Methods of system analysis. Systematic analysis of legal norms

System analysis- a scientific method of cognition, which is a sequence of actions to establish structural connections between the elements of the complex systems being studied - technical, economic, etc. It is based on a complex of general scientific, experimental, natural science, statistical, and mathematical methods. It is carried out using modern computer technology. The result of systemic research is, as a rule, the choice of a very specific alternative: a development plan, a technical system, a region, a commercial structure, etc. Therefore, the origins of system analysis and its methodological concepts lie in those disciplines that deal with decision-making problems: operations theory and general management theory and the systems approach.

The purpose of systems analysis is to streamline the sequence of actions when solving major problems, based on a systems approach. In systems analysis, problem solving is defined as an activity that maintains or improves the characteristics of a system. Techniques and methods of system analysis are aimed at advancing alternative options solving the problem, identifying the extent of uncertainty for each option and comparing options according to their effectiveness.

System analysis is based on a number of general principles, including:

the principle of deductive sequence - a sequential consideration of the system in stages: from the environment and connections with the whole to connections between parts of the whole (see the stages of system analysis in more detail below);

the principle of integrated consideration - each system must be integral as a whole, even when considering only individual subsystems of the system;

the principle of coordinating resources and review goals, updating the system;

the principle of non-conflict - the absence of conflicts between parts of the whole, leading to a conflict between the goals of the whole and the part.

2. Application of systems analysis

The scope of application of systems analysis methods is very wide. There is a classification according to which all problems to which systems analysis methods can be applied are divided into three classes:

well-structured, or quantitatively formulated, problems in which the significant dependencies are very well understood;

unstructured, or qualitatively expressed problems, containing only a description of the most important resources, features and characteristics, the quantitative relationships between which are completely unknown;

ill-structured, or mixed problems that contain both qualitative elements and little-known, uncertain aspects that tend to dominate.

To solve well-structured quantitative problems, the well-known methodology of operations research is used, which consists of constructing an adequate mathematical model (for example, problems of linear, nonlinear, dynamic programming, problems of queuing theory, game theory, etc.) and applying methods to find the optimal control strategy purposeful actions.

The use of systems analysis methods to solve these problems is necessary, first of all, because in the decision-making process it is necessary to make a choice under conditions of uncertainty, which is caused by the presence of factors that cannot be strictly quantified. In this case, all procedures and methods are aimed specifically at putting forward alternative solutions to the problem, identifying the extent of uncertainty for each of the options and comparing options according to certain performance criteria. Experts only prepare or recommend solutions, while decision-making remains within the competence of the relevant official (or body).

Decision support systems are used to solve weakly structured and unstructured problems.

Technology for solving such complex tasks can be described by the following procedure:

formulation of the problem situation;

defining goals;

defining criteria for achieving goals;

building models to justify decisions;

search for an optimal (permissible) solution;

agreement on the decision;

preparing a solution for implementation;

approval of the decision;

management of the implementation of the solution;

checking the effectiveness of the solution.

The central procedure in system analysis is the construction of a generalized model (or models) that reflects all the factors and relationships of the real situation that may appear in the process of implementing a decision. The resulting model is examined to determine the proximity of the result of applying one or another of the alternative options to the desired one, the comparative costs of resources for each option, and the degree of sensitivity of the model to various external influences.

The research is based on a number of applied mathematical disciplines and methods widely used in modern technical and economic activities related to management. These include:

methods of analysis and synthesis of control theory systems,

method of expert assessments,

critical path method,

queuing theory, etc.

The technical basis of system analysis is modern computing power and information systems created on its basis.

Methodological means used in solving problems using system analysis are determined depending on whether a single goal or a certain set of goals is being pursued, whether the decision is made by one person or several, etc. When there is one fairly clearly defined goal, the degree of achievement of which can be assessed based on one criterion; mathematical programming methods are used. If the degree of achievement of a goal must be assessed on the basis of several criteria, the apparatus of utility theory is used, with the help of which the criteria are ordered and the importance of each of them is determined. When the development of events is determined by the interaction of several individuals or systems, each of which pursues its own goals and makes its own decisions, game theory methods are used.

Despite the fact that the range of modeling and problem solving methods used in system analysis is continuously expanding, it is not identical in nature to scientific research: it is not related to the tasks of obtaining scientific knowledge in in its own sense, but represents only the application of scientific methods to solving practical management problems and pursues the goal of rationalizing the decision-making process, without excluding from this process the inevitable subjective aspects in it.

SYSTEM ANALYSIS– a set of methods and tools used in the research and design of complex and highly complex objects, primarily methods for developing, making and justifying decisions in the design, creation and management of social, economic, human-machine and technical systems . In the literature, the concept of systems analysis is sometimes identified with the concept systematic approach , but such a generalized interpretation of system analysis is hardly justified. Systems analysis emerged in the 1960s. as a result of the development of operations research and systems engineering. The theoretical and methodological basis of system analysis is the systems approach and general systems theory . System analysis is applied gl.o. to the study of artificial (arising with human participation) systems, and in such systems important role belongs to human activity. The use of systems analysis methods to solve research and management problems is necessary primarily because in the decision-making process it is necessary to make choices under conditions of uncertainty, which is associated with the presence of factors that cannot be strictly quantified. Procedures and methods of system analysis are aimed at putting forward alternative options for solving a problem, identifying the extent of uncertainty for each option and comparing options according to certain performance criteria. According to the principles of systems analysis, this or that complex problem that arises before society (primarily the problem of management) should be considered as a whole, as a system in the interaction of all its components. To make a decision about managing this system, it is necessary to determine its goal, the goals of its individual subsystems and many alternatives for achieving these goals, which are compared according to certain efficiency criteria, and as a result, the most appropriate control method for a given situation is selected. The central procedure in system analysis is the construction of a generalized model (or models) that reflects all the factors and relationships of the real situation that may appear in the process of implementing a decision. The resulting model is examined to determine the proximity of the result of applying one or another of the alternative options to the desired one, the comparative costs of resources for each option, and the degree of sensitivity of the model to various undesirable external influences. System analysis is based on a number of applied mathematical disciplines and methods widely used in modern activities management. The technical basis of system analysis is modern computers and information systems. In system analysis, methods of system dynamics, game theory, heuristic programming, simulation modeling, program-target control, etc. are widely used. Important feature system analysis is the unity of the formalized and informal means and research methods used in it.

Literature:

1. Gvishiani D.M. Organization and management. M., 1972;

2. Cleland D.,King W. System analysis and target management. M., 1974;

3. Nappelbaum E.L. Systems analysis as a scientific research program - structure and key concepts. – In the book: System Research. Methodological problems. Yearbook 1979. M., 1980;

4. Larichev O.I. Methodological problems practical application system analysis. - There; Blauberg I.V.,Mirsky E.M.,Sadovsky V.N. Systems approach and systems analysis. – In the book: System Research. Methodological problems. Yearbook 1982. M., 1982;

5. Blauberg I.V. The problem of integrity and a systematic approach. M., 1997;

6. Yudin E.G. Methodology of science. Systematicity. Activity. M., 1997.

7. See also lit. to Art. System , Systems approach.

V.N.Sadovsky

Virtual exhibition

System analysis in economics

The library and information complex of the Financial University invites you to the virtual exhibition "System Analysis in Economics", which presents publications about the laws of existence and development of society, about the application systematic approach when solving socio-economic and management problems.

From the second half of the 20th century. Tens, and perhaps hundreds of thousands of publications have appeared devoted to the study of various systems in living and inanimate nature, as well as in society. This was accompanied by numerous attempts to classify both the systems themselves and the research work aimed at studying them.

Widespread in domestic and foreign literature received the concepts of “system”, “structure”, “system analysis”, “system-structural research”, “system approach”. In strict scientific, popular science works and textbooks, these concepts were given various definitions, they were clarified, and the scope of their application was limited or expanded. However, there are still no generally accepted definitions of these concepts and clear boundaries of their applicability.

As scientific research and practical (entrepreneurial, social and political) activities become more complex, it has become quite obvious that there are significant differences between scientific research into various systems in nature and society, on the one hand, and analytical research aimed at studying systemic phenomena and processes in social sphere, business and political activity, on the other.

Scientific research is ultimately focused on the knowledge of truth, that is, the discovery of reliable laws of nature and society confirmed by experiment and observation, new facts, methodology and methods for studying them, while analytical research in social, business and political sphere are aimed at satisfying the requests of customers, that is, leaders of various public, business and political organizations and institutions.

Current level of development various industries scientific knowledge is characterized by two opposing, but not mutually exclusive, trends:

1. Differentiation is the process of separating particular sciences from general ones as a result of increasing knowledge and the emergence of new problems.

2. Integration is the process of the emergence of general sciences as a result of the generalization of knowledge and the development of individual parts of related sciences and their methods. As a result of these processes, a fundamentally new subject area emerged scientific activity- systems research.

Systems research includes operations research, cybernetics, systems engineering, systems analysis, and systems theory. System analysis is a modern scientific direction of the integration type, which develops a systemic methodology for decision-making and occupies a certain place in the structure of modern systems research.

System analysis is implemented in various subject areas - economics and management, technology, production, computer science, etc. The main goal of system analysis is to find ways out of a problem situation in the subject area under consideration. As a result of implementing system analysis procedures, a methodology for solving complex problems is obtained. In the process of creating the methodology, the basic principles of systems theory, systems approach, operations research apparatus, cybernetics and systems engineering are used.

One of the main needs of business is a quantitative justification for one or another management decision. This need is most fully satisfied by the developments of the scientific discipline “operations research”. The purpose of the discipline "operations research" is a comprehensive analysis of the problem and its solution through the use of optimization mathematical models. Operations research has a close relationship with another discipline in the systems research cycle - systems analysis.

System analysis in enterprise management is also aimed at finding well-founded (ideally, quantitatively justified) management decisions. Quantitative justification for a decision makes it easier to select the best alternative from many available ones. The right of final choice in the process of making an optimal management decision belongs to the managerial decision maker (DM). An operation is any activity aimed at achieving a specific goal. Indirectly, the degree of achievement of the goal can be assessed through the performance indicators of the enterprise.

Efficiency is the relationship between the result and the costs of obtaining it. Performance indicators are a group of parameters that characterize the efficiency of an operation or the efficiency of a system. Performance criterion is a preferred performance indicator out of many acceptable ones. Performance criteria can be both qualitative and quantitative. If there is information about the object of management and the parameters of the external environment, we can say that management decisions are made under conditions of certainty.

The characteristics of the control object are specified using controlled and uncontrolled variables. Managed Variables ( decision variables) - quantitatively measurable quantities and characteristics with the help of which the decision maker can exercise control. An example is production volumes, raw material reserves, etc. Uncontrollable variables (parameters) are factors that the decision maker is not able to influence or change, for example, market capacity, actions of competitors. In the process of studying complex systems, their composition, structure, type of connections between elements, as well as between the system and the external environment, and the behavior of the system under various management influences are studied. But not all complex systems (especially socio-economic ones) can experience various management influences. To overcome this difficulty, models are used in the study of complex systems.

Model is an object that reflects the most important characteristics of the process or system under study, created to obtain additional information about a given process or system. To assess the quantitative impact of controlled variables on the effectiveness criterion, it is necessary to create mathematical model control object. A mathematical model is a logical-mathematical relationship that establishes a connection between the characteristics of a control object and the efficiency criterion.

In the process of constructing an economic-mathematical model, the economic essence of the problem is written using various characters, variable and constant quantities, indices and other notations. In other words, the management situation is formalized. All conditions of the problem must be written in the form of equations or inequalities. When formalizing management situations, first of all, a system of variables is determined. In economic problems, the variables or required quantities are: the volume of production at the enterprise, the amount of cargo transported by suppliers to specific consumers, etc.

It is hardly possible to classify all situations of economic management in which the need for system analysis arises. It should be noted the most common types of management situations in which it is possible to use system analysis:

1. Solving new problems. With the help of system analysis, the problem is formulated, it is determined what and what needs to be known, who should know.

2. Solving a problem involves linking goals with multiple means of achieving them.

3. The problem has ramified connections that cause long-term consequences in different sectors of the national economy, and making a decision on them requires taking into account the full efficiency and full costs.

4. Solving problems in which there are various difficult to compare options for solving a problem or achieving an interrelated set of goals.

5. Cases when national economy Entirely new systems are created or old systems are radically restructured.

6. Cases when improvement, improvement, reconstruction of production or economic relations is carried out.

7. Problems associated with automation of production, and especially management, in the process of creating automated control systems at any level.

8. Work to improve methods and forms of economic management, because it is known that none of the methods of economic management operates on its own, but only in a certain combination, in interrelation.

9. Cases when improvement of the organization of production or management is carried out at unique, atypical objects, distinguished by the great specificity of their activities, where it is impossible to act by analogy.

10. Cases where decisions made for the future, the development of a development plan or program must take into account the factor of uncertainty and risk.

11. Cases when planning or making responsible decisions on development directions is made for a fairly distant future.

Antonov, A.V. System analysis: textbook / A.V. Antonov.-M.: Higher School, 2004.-454 p. (full text).

Anfilatov, V.S. System analysis in management: textbook / V.S. Anfilatov, A.A. Emelyanov, A.A. Kukushkin.-M.: Finance and Statistics, 2002.-368 p. (full text).

Berg, D. B. System analysis of competitive strategies: textbook / D. B. Berg, S. N. Lapshina. - Ekaterinburg: Ural Publishing House. University, 2014.- 56 p. (full text).

Volkova, V.N. Fundamentals of systems theory and system analysis: textbook / V.N. Volkova, A.A. Denisov.—2nd ed., revised. and additional - St. Petersburg: St. Petersburg State Technical University Publishing House, 2001. - 512 p. (full text).

Volkova, V.N. Systems theory and system analysis: textbook for bachelors / V.N. Volkova, A.A. Denisov.-M.: YURAYT, 2012.-679 p. (abstract, introduction, table of contents).

Gerasimov, B.I. Fundamentals of the theory of system analysis: quality and choice: textbook / B.I. Gerasimov, G.L. Popova, N.V. Zlobina. - Tambov: Publishing house of the Federal State Budgetary Educational Institution of Higher Professional Education "TSTU", 2011. - 80 p. (full text).

Germeyer, Yu.B. Introduction to the theory of operations research / Yu.B. Germeyer.-M.: Nauka, 1971.-384 p. (full text).

Drogobytsky, I.G. System analysis in economics: textbook.-2 ed., revised. and additional - M.: UNITY-DANA, 2011.- 423 pp. (full text).

Ivanilov, Yu.P. Mathematical models in economics: textbook / Yu.P. Ivanilov, A.V. Lotov.-M.: Nauka, 1979.-304 p. (full text).

Intriligator, M. Mathematical methods of optimization and economic theory / translated from English. edited by A.A. Konyusa.-M.: Progress, 1975.-598 p. (full text).

Kaluzhsky, M.L. General theory of systems: textbook / M.L. Kaluzhsky.-M.: Direct-Media, 2013.-177 pp. (full text).

Katalevsky, D.Yu. Fundamentals of simulation modeling and system analysis in management: textbook / D.Yu. Katalevsky.-M.: Publishing house Mosk. Univ., 2011.-304 p. (full text).

Kozlov, V.N. System analysis, optimization and decision making: textbook /V. N. Kozlov. - St. Petersburg. : Publishing House Polytechnic. University, 2011.- 244 p. (full text).

Kolomoets, F.G. Fundamentals of system analysis and decision-making theory: a manual for researchers, managers and university students / F.G. Kolomoets.-Mn.: Theseus, 2006.-320 p. (full text).

Lecture notes on the discipline “Theoretical analysis of economic systems” / Kazan Federal University (full text).

Moiseev, N.N. Mathematical problems of system analysis: textbook / N.N. Moiseev.-M.: Nauka, 1981 (full text).

Novoseltsev, V.I. System analysis: modern concepts / V.I. Novoseltsev.-2 ed., revised. and additional). - Voronezh: Kvarta, 2003. - 360 pages (full text).

Ostroukhova N.G. System analysis in economics and enterprise management: Textbook. allowance / N.G. Ostroukhova. - Saratov: KUBiK Publishing House, 2014. - 90 p. (full text).

Peregudov, F.I. Introduction to system analysis: textbook / F.I. Peregudov, F.P. Tarasenko.-M.: Higher School, 1989.-360 p. (full text).

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Lecture 1: System analysis as a methodology for problem solving

It is necessary to be able to think abstractly in order to perceive the world around us in a new way.

R. Feynman

One of the directions of restructuring in higher education is to overcome the shortcomings of narrow specialization, strengthen interdisciplinary connections, develop a dialectical vision of the world, and systems thinking. The curriculum of many universities has already introduced general and special courses that implement this trend: for engineering specialties - “design methods”, “systems engineering”; for military and economic specialties - “operations research”; in administrative and political management - “political science”, “futurology”; in applied scientific research - “simulation modeling”, “experimental methodology”, etc. Among these disciplines is a course in systems analysis - a typically inter- and supradisciplinary course that generalizes the methodology for studying complex technical, natural and social systems.

1.1 System analysis in the structure of modern systems research

Currently, two opposing trends are observed in the development of sciences:

1. Differentiation, when, with an increase in knowledge and the emergence of new problems, special sciences are separated from more general sciences.
2. 2. Integration, when more general sciences arise as a result of the generalization and development of certain sections of related sciences and their methods.

The processes of differentiation and integration are based on 2 fundamental principles of materialist dialectics:

1. the principle of qualitative originality of various forms of motion of matter, def. the need to study certain aspects of the material world;
2. principle of material unity of the world, def. the need to obtain a holistic understanding of any objects of the material world.

As a result of the integrative trend, a new area of ​​scientific activity has emerged: systems research, which is aimed at solving complex large-scale problems of great complexity.

Within the framework of systems research, such integration sciences are being developed as: cybernetics, operations research, systems engineering, systems analysis, artificial intelligence and others. Those. we are talking about creating a 5th generation computer (to remove all intermediaries between the computer and the machine. The user is unqualified), an intelligent interface is used.

Systems analysis develops a system methodology for solving complex applied problems, based on the principles of the systems approach and general systems theory, development and methodologically generalizing the conceptual (ideological) and mathematical apparatus of cybernetics, operations research and systems engineering.

System analysis is a new scientific direction of the integration type, which develops a systemic methodology for decision-making and occupies a certain place in the structure of modern systems research.

Fig.1.1 - System analysis

1. systems research
2. systems approach
3. specific system concepts
4. general systems theory (metatheory in relation to specific systems)
5. dialectical materialism (philosophical problems of systems research)
6. scientific system theories and models (the doctrine of the earth's biosphere; probability theory; cybernetics, etc.)
7. technical systems theories and developments—operations research; systems engineering, systems analysis, etc.
8. particular theories of the system.

1.2 Classification of problems according to the degree of their structuring

According to the classification proposed by Simon and Newell, the entire set of problems, depending on the depth of their knowledge, is divided into 3 classes:

1. well-structured or quantitatively expressed problems that can be mathematically formalized and solved using formal methods;
2. unstructured or qualitatively expressed problems that are described only at the content level and are solved using informal procedures;
3. weakly structured (mixed problems), which contain quantitative and qualitative problems, and the qualitative, little-known and uncertain aspects of the problems tend to be domainized.

These problems are solved through the integrated use of formal methods and informal procedures. The classification is based on the degree of structuring of problems, and the structure of the entire problem is determined by 5 logical elements:

1. a goal or series of goals;
2. alternatives for achieving goals;
3. resources spent on implementing alternatives;
4. model or series of models;
5. 5.criterion for choosing the preferred alternative.

The degree of structuring of the problem is determined by how well the specified elements of the problem are identified and understood.

It is typical that the same problem can occupy different places in the classification table. In the process of ever deeper study, comprehension and analysis, the problem can turn from unstructured to weakly structured, and then from weakly structured to structured. In this case, the choice of method for solving a problem is determined by its place in the classification table.

Fig.1.2 - Classification table

1. identifying the problem;
2. formulation of the problem;
3. solution to the problem;
4. unstructured problem (can be solved using heuristic methods);
5. methods expert assessments;
6. poorly structured problem;
7. systems analysis methods;
8. well structured problem;
9. operations research methods;
10. decision-making;
11. implementation of the solution;
12. evaluation of the solution.

1.3 Principles for solving well-structured problems

To solve problems of this class, mathematical methods of I.O. are widely used. In operational research, the main stages can be distinguished:

1. Identifying competing strategies to achieve a goal.
2. Construction of a mathematical model of the operation.
3. Evaluating the effectiveness of competing strategies.
4. Choosing the optimal strategy for achieving goals.

The mathematical model of the operation is a functional:

E = f(x∈x → , (α), (β)) ⇒ extz

• E - criterion for the effectiveness of operations;
• x is the strategy of the operating party;
• α is the set of conditions for carrying out operations;
• β is the set of environmental conditions.

The model allows you to evaluate the effectiveness of competing strategies and select the optimal strategy from among them.

1. persistence of the problem
2. restrictions
3. operational efficiency criterion
4. mathematical model of the operation
5. model parameters, but some of the parameters are usually unknown, therefore (6)
6. forecasting information (i.e. you need to predict a number of parameters)
7. competing strategies
8. analysis and strategies
9. optimal strategy
10. approved strategy (simpler, but which also satisfies a number of criteria)
11. implementation of the solution
12. model adjustment

The criterion for the effectiveness of an operation must satisfy a number of requirements:

1. Representativeness, i.e. the criterion should reflect the main, and not the secondary, purpose of the operation.
2. Criticality - i.e. the criterion must change when the operation parameters change.
3. Uniqueness, since only in this case is it possible to find a rigorous mathematical solution to the optimization problem.
4. Taking into account stochasticity, which is usually associated with the random nature of some operation parameters.
5. Accounting for uncertainty, which is associated with the lack of any information about certain parameters of operations.
6. Taking into account the counteraction that is often caused by a conscious enemy who controls the full parameters of operations.
7. Simple, because a simple criterion allows you to simplify the mathematical calculations when searching for opt. solutions.

We present a diagram that illustrates the basic requirements for the effectiveness criterion of operations research.

Rice. 1.4 — Diagram that illustrates the requirements for an operations research performance criterion

1. statement of the problem (2 and 4 (limitations) follow);
2. efficiency criterion;
3. top level tasks
4. restrictions (we organize nesting of models);
5. communication with top-level models;
6. representativeness;
7. criticality;
8. uniqueness;
9. taking into account stochasticity;
10. accounting for uncertainty;
11. taking into account counteraction (game theory);
12. simplicity;
13. mandatory restrictions;
14. additional restrictions;
15. artificial restrictions;
16. selection of the main criterion;
17. translation of restrictions;
18. construction of a generalized criterion;
19. assessment of mathematical performance;
20. constructing confidence intervals:
21. analysis of possible options (there is a system; we do not know exactly what the intensity of the input flow is; we can only assume one or another intensity with a certain probability; then we weigh the output options).

Uniqueness - so that the problem can be solved using strictly mathematical methods.

Points 16, 17 and 18 are methods that allow you to get rid of multi-criteria.

Accounting for stochasticity - most of the parameters have a stochastic value. In some cases stoch. we ask in form distribution, therefore, the criterion itself must be averaged, i.e. apply mathematical expectations, therefore, paragraphs 19, 20, 21.

1.4 Principles for solving unstructured problems

To solve problems of this class, it is advisable to use expert assessment methods.

Expert assessment methods are used in cases where the mathematical formalization of problems is either impossible due to their novelty and complexity, or requires a lot of time and money. Common to all methods of expert assessments is the appeal to the experience, guidance and intuition of specialists performing the functions of experts. Giving answers to the question posed, experts are, as it were, sensors of information that is analyzed and summarized. It can be argued, therefore: if there is a true answer in the range of answers, then a set of disparate opinions can be effectively synthesized into some generalized opinion close to reality. Any method of expert assessments is a set of procedures aimed at obtaining information of heuristic origin and processing this information using mathematical and statistical methods.

The process of preparing and conducting the examination includes the following stages:

1. definition of chains of examination;
2. formation of a group of specialist analysts;
3. formation of a group of experts;
4. development of examination scenario and procedures;
5. collection and analysis of expert information;
6. processing of expert information;
7. analysis of examination results and decision-making.

When forming a group of experts, it is necessary to take into account their individual characteristics, which affect the results of the examination:

• competence (level of professional training)
• creativity (human creative abilities)
• constructive thinking (don’t “fly” in the clouds)
• conformism (susceptibility to the influence of authority)
• attitude towards examination
• collectivism and self-criticism

Expert assessment methods are used quite successfully in the following situations:

• selection of goals and topics of scientific research
• selection of options for complex technical and socio-economic projects and programs
• construction and analysis of models of complex objects
• construction of criteria in vector optimization problems
• classification of homogeneous objects according to the degree of expression of any property
• assessment of product quality and new technology
• decision making in production management problems
• long-term and current production planning, research and development work
• scientific, technical and economic forecasting, etc. and so on.

1.5 Principles for solving semi-structured problems

To solve problems of this class, it is advisable to use systems analysis methods. Problems solved using system analysis have a number of characteristic features:

1. the decision being made relates to the future (a plant that does not exist yet)
2. there is a wide range of alternatives
3. solutions depend on current incomplete technological advances
4. decisions made require large investments of resources and contain elements of risk
5. Requirements related to cost and time to resolve the problem are not fully defined
6. the internal problem is complex due to the fact that its solution requires a combination of various resources.

The basic concepts of systems analysis are as follows:

• the process of solving a problem should begin with identifying and justifying the final goal that they want to achieve in a particular area, and on this basis intermediate goals and objectives are determined
• any problem must be approached as a complex system, identifying all possible sub-problems and relationships, as well as the consequences of certain decisions
• in the process of solving a problem, many alternatives to achieve the goal are formed; evaluating these alternatives using appropriate criteria and selecting the preferred alternative
• The organizational structure of a problem-solving mechanism must be subordinated to a goal or set of goals, and not vice versa.

System analysis is a multi-step iterative process, and the starting point of this process is the formulation of the problem in some initial form. When formulating a problem, it is necessary to take into account 2 conflicting requirements:

1. the problem should be formulated broadly enough so that nothing essential is missed;
2. the problem must be formed in such a way that it is visible and can be structured. In the course of system analysis, the degree of structuring of the problem increases, i.e. the problem is formulated more and more clearly and comprehensively.

Rice. 1.5 - One step of system analysis

1. formulation of the problem
2. rationale for the purpose
3. formation of alternatives
4. resource research
5. building a model
6. evaluation of alternatives
7. decision making (choosing one solution)
8. sensitivity analysis
9. verification of source data
10. clarification of the final goal
11. search for new alternatives
12. analysis of resources and criteria

1.6 Main stages and methods of SA

SA provides for: development of a systematic method for solving the problem, i.e. a logically and procedurally organized sequence of operations aimed at selecting a preferred solution alternative. SA is implemented practically in several stages, but there is still no unity regarding their number and content, because There is a wide variety of applied problems.

Here is a table that illustrates the main patterns of SA 3 different scientific schools.

Main stages of system analysis
According to F. Hansman Germany, 1978	According to D. Jeffers USA, 1981	According to V.V. Druzhinin USSR, 1988
General orientation to the problem (outline statement of the problem) Selecting Appropriate Criteria Formation alternative solutions Identification of significant environmental factors Model building and testing Estimation and forecast of model parameters Getting information from the model Preparing to choose a solution Implementation and control	Selecting a problem Statement of the problem and limiting the degree of its complexity Establishing hierarchy, goals and objectives Choosing ways to solve a problem Modeling Assessing possible strategies Implementation of results	Isolating the problem Description Setting criteria Idealization (extreme simplification, attempt to build a model) Decomposition (breaking down into parts, finding solutions in parts) Composition (“gluing” parts together) Making the best decision

The scientific tools of SA include the following methods:

• scripting method (trying to describe the system)
• goal tree method (there is final goal, it is divided into subgoals, subgoals into problems, etc., i.e. decomposition to problems that we can solve)
• morphological analysis method (for inventions)
• expert assessment methods
• probabilistic and statistical methods (theory of MO, games, etc.)
• cybernetic methods (object in the form of a black box)
• IR methods (scalar opt)
• vector optimization methods
• simulation methods (for example, GPSS)
• network methods
• matrix methods
• methods of economic analysis, etc.

In the SA process, various methods are used at different levels, in which heuristics are combined with formalism. CA serves as a methodological framework that combines all the necessary methods, research techniques, activities and resources for solving problems.

1.7 System of preferences of decision-makers and a systematic approach to the decision-making process.

The decision-making process consists of choosing a rational solution from a certain set of alternative solutions, taking into account the decision-maker’s system of preferences. Like any process in which a person participates, it has 2 sides: objective and subjective.

The objective side is what is really outside the human consciousness, and the subjective side is what is reflected in the human consciousness, i.e. objective in the human mind. The objective is not always reflected in a person’s consciousness quite adequately, but it does not follow from this that there cannot be correct decisions. A practically correct decision is one that in its main features correctly reflects the situation and corresponds to the task at hand.

The decision maker’s preference system is determined by many factors:

• understanding the problem and development prospects;
• current information about the status of some operation and external conditions its course;
• directives from higher authorities and various kinds of restrictions;
• legal, economic, social, psychological factors, traditions, etc.

Rice. 1.6 — System of preferences for decision makers

1. directives from higher authorities on the goals and objectives of operations (technical processes, forecasting)
2. restrictions on resources, degree of independence, etc.
3. information processing
4. operation
5. external conditions (external environment), a) determination; b) stochastic (the computer fails after a random interval t); c) organized opposition
6. information about external conditions
7. rational decision
8. control synthesis (system dependent)

Being in this grip, the decision maker must normalize the many potentially possible solutions from them. Of these, select 4-5 best and from them - 1 solution.

A systematic approach to the decision-making process consists of implementing 3 interrelated procedures:

1. Many potential solutions are highlighted.
2. From among them, many competing solutions are selected.
3. A rational solution is selected taking into account the decision maker’s system of preferences.

Rice. 1.7 — Systematic approach to the decision-making process

1. possible solutions
2. competing solutions
3. rational decision
4. purpose and objectives of the operation
5. operation status information
6. information about external conditions
   1. stochastic
   2. organized opposition
7. resource limitation
8. limitation on the degree of independence
9. additional restrictions and conditions
   1. legal factors
   2. economic forces
   3. sociological factors
   4. psychological factors
   5. traditions and more
10. performance criterion

Modern systems analysis is an applied science aimed at identifying the causes of real difficulties that arose before the “problem owner” and developing options for eliminating them. In its most developed form, system analysis also includes direct, practical improving intervention in a problem situation.

Systematicity should not seem like some kind of innovation, the latest achievement of science. Consistency is a universal property of matter, the form of its existence, and therefore an integral property of human practice, including thinking. Any activity can be less or more systematic. The appearance of a problem is a sign of insufficient systematicity; the solution to the problem is the result of increased systematicity. Theoretical thought at different levels of abstraction reflected the systematic nature of the world in general and the systematic nature of human cognition and practice. At the philosophical level it is dialectical materialism, at the general scientific level it is systemology and general theory of systems, theory of organization; in natural sciences - cybernetics. With the development of computer technology, computer science and artificial intelligence emerged.

In the early 80s, it became obvious that all these theoretical and applied disciplines form a kind of single stream, a “systemic movement.” Consistency becomes not only a theoretical category, but also a conscious aspect of practical activity. Since large and complex systems have necessarily become the subject of study, management and design, a generalization of methods for studying systems and methods of influencing them was required. A certain applied science had to emerge, which would be a “bridge” between abstract theories of systematicity and living systemic practice. It arose - first, as we noted, in various fields and under different names, and in recent years it has formed into a science that is called “system analysis.”

The features of modern systems analysis arise from the very nature of complex systems. Having as a goal the elimination of a problem or, at a minimum, the clarification of its causes, system analysis involves a wide range of means for this purpose, using the capabilities of various sciences and practical fields of activity. Being essentially an applied dialectic, systems analysis attaches great importance to the methodological aspects of any systems research. On the other hand, the applied orientation of system analysis leads to the use of all modern means scientific research - mathematics, computer technology, modeling, field observations and experiments.

In the course of studying a real system, one usually encounters a wide variety of problems; It is impossible for one person to be a professional in each of them. The solution seems to be that whoever undertakes to carry out system analysis has the education and experience necessary to identify and classify specific problems, to determine which specialists should be contacted to continue the analysis. This presents special requirements to system specialists: they must have broad erudition, relaxed thinking, the ability to attract people to work, and organize collective activities.

After listening to a real course of lectures, or reading several books on this topic, you cannot become a specialist in systems analysis. As W. Shakespeare put it: “If doing were as easy as knowing what to do, chapels would be cathedrals, huts palaces.” Professionalism is acquired through practice.

Let's consider an interesting forecast of the most rapidly expanding areas of employment in the United States: Dynamics in % 1990-2000.

• nursing staff - 70%
• Radiation technology specialists - 66%
• travel agents - 54%
• computer systems analysts - 53%
• programmers - 48%
• electronics engineers - 40%

Development of system views

What does the word “system” or “large system” mean, what does it mean to “act systematically”? We will receive answers to these questions gradually, increasing the level of systematicity of our knowledge, which is the goal of this course of lectures. For now, we have enough of those associations that arise when using the word “system” in ordinary speech in combination with the words “socio-political”, “Solar”, “nervous”, “heating” or “equations”, “indicators”, “views” and beliefs." Subsequently, we will consider in detail and comprehensively the signs of systematicity, but now we will note only the most obvious and obligatory of them:

• structure of the system;
• interconnectedness of its constituent parts;
• subordination of the organization of the entire system to a specific goal.

Systematicity of practical activities

In relation, for example, to human activity, these signs are obvious, since each of us can easily detect them in our own practical activities. Every conscious action we take pursues a very specific goal; in any action it is easy to see its component parts, smaller actions. In this case, the components are performed not in any random order, but in a certain sequence. This is a specific, goal-oriented interconnectedness components, which is a sign of systematicity.

Systematic and algorithmic

Another name for this type of activity is algorithmic. The concept of an algorithm arose first in mathematics and meant specifying a precisely defined sequence of unambiguously understood operations on numbers or other mathematical objects. In recent years, the algorithmic nature of any activity has begun to be realized. They are already talking not only about algorithms for making management decisions, about learning algorithms, and algorithms for playing chess, but also about algorithms for invention, algorithms for music composition. We emphasize that in this case a departure is made from the mathematical understanding of the algorithm: while maintaining the logical sequence of actions, it is allowed that the algorithm may contain unformalized actions. Thus, explicit algorithmization of any practical activity is an important property of its development.

Systematicity of cognitive activity

One of the features of cognition is the presence of analytical and synthetic modes of thinking. The essence of analysis is to divide the whole into parts, to present the complex as a collection of simpler components. But in order to understand the whole, the complex, the reverse process is also necessary - synthesis. This applies not only to individual thinking, but also to universal human knowledge. Let's just say that the division of thinking into analysis and synthesis and the interconnectedness of these parts are the most important sign of the systematic nature of cognition.

Systematicity as a universal property of matter

Here it is important for us to highlight the idea that consistency is not only a property of human practice, including external active activity and thinking, but a property of all matter. The systematic nature of our thinking follows from the systematic nature of the world. Modern scientific data and modern systemic concepts allow us to talk about the world as an endless hierarchical system of systems that are in development and at different stages of development, at different levels of the system hierarchy.

Summarize

In conclusion, as food for thought, we present a diagram depicting the connection between the issues discussed above.

Fig 1.8 - Connection of the issues discussed above

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• Introduction 2
• 1. The essence of the systems approach as the basis of system analysis 5
• 1.1 Contents and characteristics of the systems approach 5
• 1. 2 Basic principles of the systems approach 8
• 2.Basic elements of system analysis 11
• 2. 1 Conceptual apparatus of system analysis 11
• 2. 2 Principles of systems analysis 15
• 2. 3 Methods of system analysis 20
• Conclusion 29
• Literature 31
• Introduction
• In the context of the dynamism of modern production and society, management must be in a state of continuous development, which today cannot be achieved without researching trends and opportunities, without choosing alternatives and directions for development, performing management functions and methods of making management decisions. The development and improvement of an enterprise is based on a thorough and deep knowledge of the organization’s activities, which requires a study of management systems.
• Research is carried out in accordance with the chosen purpose and in a certain sequence. Research is an integral part of an organization's management and is aimed at improving the basic characteristics of the management process. When conducting research on control systems, the object of study is the control system itself, which is characterized by certain characteristics and is subject to a number of requirements.
• The effectiveness of control systems research is largely determined by the research methods chosen and used. Research methods are methods and techniques for conducting research. Their competent use contributes to obtaining reliable and complete results from the study of problems that have arisen in the organization. Selection of research methods, integration various methods when conducting research, it is determined by the knowledge, experience and intuition of the specialists conducting the research.
• To identify the specifics of the work of organizations and develop measures to improve production and economic activities, system analysis is used. The main goal of system analysis is the development and implementation of a control system that is selected as a reference system that best meets all the requirements for optimality. System analysis is complex in nature and is based on a set of approaches, the use of which will allow the analysis to be carried out in the best way and obtain the desired results. To successfully carry out the analysis, it is necessary to select a team of specialists who are well acquainted with the methods of economic analysis and production organization.
• Trying to understand a system of great complexity, consisting of many subsystems that are diverse in characteristics and, in turn, complex, scientific knowledge follows the path of differentiation, studying the subsystems themselves and ignoring their interaction with the large system in which they are included and which has a decisive impact on the entire system. the global system as a whole. But complex systems are not reduced to the simple sum of their parts; in order to understand integrity, its analysis must certainly be supplemented by a deep systemic synthesis; an interdisciplinary approach and interdisciplinary research are needed here, a completely new scientific toolkit is required.
• The relevance of the chosen topic of the course work lies in the fact that in order to comprehend the laws governing human activity, it is important to learn to understand how in each specific case the general context of perception of the next tasks is formed, how to bring into the system (hence the name “system analysis”) initially scattered and redundant information about the problem situation, how to harmonize with each other and derive one from another the ideas and goals of different levels related to a single activity.
• Here lies a fundamental problem that affects almost the very foundations of the organization of any human activity. The same task in different contexts, at different levels of decision-making, requires completely different methods of organization and different knowledge. During the transition, as the action plan is fleshed out from one level to another, the formulations of both the main goals and the main principles on which their achievement is based are radically transformed. And finally, at the stage of distributing limited common resources between individual programs, it is necessary to compare what is fundamentally incomparable, since the effectiveness of each program can only be assessed according to some criterion inherent to it alone.
• The systems approach is one of the most important methodological principles of modern science and practice. System analysis methods are widely used to solve many theoretical and applied problems.
• The main objectives of the course work are to study the essence of the systems approach, as well as the basic principles and methods of systems analysis.
• 1. The essence of the systems approach as the basis of systems analysis

1 Contents and characteristics of the systems approach

Since the middle of the 20th century. Intensive developments are underway in the field of systems approach and general systems theory. The systematic approach developed by solving a triune problem: accumulation in general scientific concepts and concepts latest results social, natural and technical sciences relating to the systemic organization of objects of reality and ways of knowing them; integration of the principles and experience of the development of philosophy, primarily the results of the development of the philosophical principle of systematicity and related categories; application of the conceptual apparatus and modeling tools developed on this basis to solve current complex problems.

SYSTEM APPROACH is a methodological direction in science, the main task of which is to develop methods for research and design of complex objects - systems of different types and classes. The systems approach represents a certain stage in the development of methods of cognition, methods of research and design activities, methods of describing and explaining the nature of analyzed or artificially created objects.

Currently, the systems approach is increasingly being used in management, and experience is accumulating in constructing system descriptions of research objects. The need for a systems approach is due to the enlargement and complexity of the systems being studied, the need to manage large systems and integrate knowledge.

"System" is a Greek word (systema), literally meaning a whole made up of parts; a set of elements that are in relationships and connections with each other and form a certain integrity, unity.

From the word “system” you can form other words: “systemic”, “systematize”, “systematic”. In a narrow sense, a systems approach will be understood as the use of systems methods to study real physical, biological, social and other systems.

The systems approach in a broad sense also includes the use of system methods to solve problems of systematics, planning and organizing a complex and systematic experiment.

The term "systems approach" covers a group of methods by which a real object is described as a collection of interacting components. These methods are developed within the framework of individual scientific disciplines, interdisciplinary syntheses and general scientific concepts.

The general objectives of systems research are analysis and synthesis of systems. In the process of analysis, the system is isolated from the environment, its composition is determined,
structures, functions, integral characteristics (properties), as well as system-forming factors and relationships with the environment.

In the process of synthesis, a model of a real system is created, the level of abstract description of the system is increased, the completeness of its composition and structures, description bases, patterns of dynamics and behavior are determined.

The systems approach is applied to sets of objects, individual objects and their components, as well as to the properties and integral characteristics of objects.

A systems approach is not an end in itself. In each specific case, its use should give a real, quite tangible effect. A systematic approach allows us to identify gaps in knowledge about a given object, detect their incompleteness, determine the tasks of scientific research, and in some cases - through interpolation and extrapolation - predict the properties of the missing parts of the description. There are several types of systems approach: complex, structural, holistic.

It is necessary to determine the scope of these concepts.

An integrated approach suggests the presence of a set of object components or applied research methods. In this case, neither the relationships between objects, nor the completeness of their composition, nor the relationships of the components as a whole are taken into account. Mainly static problems are solved: quantitative ratio of components and the like.

The structural approach offers the study of the composition (subsystems) and structures of an object. With this approach, there is still no correlation between subsystems (parts) and the system (whole). The decomposition of systems into subsystems is not carried out in a uniform way. The dynamics of structures, as a rule, are not considered.

In a holistic approach, relationships are studied not only between the parts of an object, but also between the parts and the whole. The decomposition of the whole into parts is unique. So, for example, it is customary to say that “the whole is something from which nothing can be taken away and to which nothing can be added.” The holistic approach offers the study of the composition (subsystems) and structures of an object not only in statics, but also in dynamics, i.e. it offers the study of the behavior and evolution of systems. The holistic approach is not applicable to all systems (objects). but only to those that are characterized by a high degree of functional independence. The most important tasks of the systems approach include:

1) development of means of representing researched and constructed objects as systems;

2) construction of generalized models of the system, models of different classes and specific properties of systems;

3) study of the structure of systems theories and various system concepts and developments.

In systems research, the analyzed object is considered as a certain set of elements, the interconnection of which determines the integral properties of this set. The main emphasis is on identifying the variety of connections and relationships that take place both within the object under study and in its relationships with the external environment. The properties of an object as an integral system are determined not only and not so much by the summation of the properties of its individual elements, but by the properties of its structure, special system-forming, integrative connections of the object under consideration. To understand the behavior of systems, primarily goal-oriented, it is necessary to identify the control processes implemented by a given system - forms of information transfer from one subsystem to another and ways of influencing some parts of the system on others, coordination of the lower levels of the system by elements of its higher level, control, influence on the last of all other subsystems. Significant importance in the systems approach is given to identifying the probabilistic nature of the behavior of the objects under study. An important feature of the systems approach is that not only the object, but also the research process itself acts as a complex system, the task of which, in particular, is to combine into a single whole various models object. Finally, system objects, as a rule, are not indifferent to the process of their research and in many cases can have a significant impact on it.

1. 2 Basic principles of the systems approach

The main principles of the systems approach are:

1. Integrity, which allows us to simultaneously consider the system as a single whole and at the same time as a subsystem for higher levels. 2. Hierarchical structure, i.e. the presence of a plurality (at least two) of elements located on the basis of the subordination of lower-level elements to higher-level elements. The implementation of this principle is clearly visible in the example of any specific organization. As you know, any organization is an interaction of two subsystems: the managing and the managed. One is subordinate to the other. 3. Structuring, which allows you to analyze the elements of the system and their relationships within a specific organizational structure. As a rule, the process of functioning of a system is determined not so much by the properties of its individual elements as by the properties of the structure itself.

4. Multiplicity, which allows the use of many cybernetic, economic and mathematical models to describe individual elements and the system as a whole.

As noted above, with a systems approach, the study of the characteristics of an organization as a system becomes important, i.e. characteristics of "input", "process" and characteristics of "output".

In a systematic approach based on marketing research, the “output” parameters are first examined, i.e. goods or services, namely what to produce, with what quality indicators, at what costs, for whom, in what time frame to sell and at what price. Answers to these questions must be clear and timely. The “output” should ultimately be competitive products or services. Then the input parameters are determined, i.e. the need for resources (material, financial, labor and information) is examined, which is determined after a detailed study of the organizational and technical level of the system under consideration (level of equipment, technology, features of the organization of production, labor and management) and parameters of the external environment (economic, geopolitical, social, environmental and etc.).

And finally, no less important is the study of the parameters of the process that converts resources into finished products. At this stage, depending on the object of study, production technology or management technology, as well as factors and ways of improving it, are considered.

Thus, the systems approach allows us to comprehensively assess any production and economic activity and the activity of the management system at the level of specific characteristics. This will help analyze any situation within a single system, identifying the nature of the input, process and output problems.

The use of a systems approach allows us to best organize the decision-making process at all levels in the management system. An integrated approach involves taking into account both internal and external environment organizations. This means that it is necessary to take into account not only internal, but also external factors- economic, geopolitical, social, demographic, environmental, etc. Factors - important aspects when analyzing organizations and, unfortunately, are not always taken into account. For example, social issues are often not taken into account or postponed when designing new organizations. When introducing new technology, ergonomic indicators are not always taken into account, which leads to increased fatigue of workers and, ultimately, to a decrease in labor productivity. When forming new labor collectives Social and psychological aspects, in particular, problems of labor motivation, are not properly taken into account. Summarizing what has been said, it can be argued that A complex approach is a necessary condition when solving the problem of analyzing an organization.

The essence of the systems approach has been formulated by many authors. In its expanded form, it was formulated by V. G. Afanasyev, who identified a number of interrelated aspects that, together and unified, constitute a system approach: - system-element approach, answering the question of what (what components) the system is formed from;

system-structural, revealing the internal organization of the system, the way of interaction of its constituent components;

- system-functional, showing what functions the system and its constituent components perform;

system-communication, revealing the relationship of a given system with others, both horizontally and vertically;

system-integrative, showing mechanisms, factors for maintaining, improving and developing the system;

Systemic-historical, answering the question of how, in what way the system arose, what stages it went through in its development, what are its historical prospects. The rapid growth of modern organizations and their level of complexity, the variety of operations performed have led to the fact that the rational implementation of management functions has become extremely difficult, but at the same time even more important for successful work enterprises. To cope with the inevitable increase in the number of operations and their complexity, a large organization must base its activities on a systems approach. Through this approach, the manager can more effectively integrate his activities in managing the organization.

The systematic approach contributes, as already mentioned, mainly to the development correct method thinking about the management process. A leader must think in accordance with a systems approach. When studying a systems approach, a way of thinking is instilled that, on the one hand, helps eliminate unnecessary complexity, and on the other, helps the manager understand the essence of complex problems and make decisions based on a clear understanding of the environment. It is important to structure the task and outline the boundaries of the system. But it is equally important to consider that the systems that a manager encounters in the course of his activities are part of larger systems, perhaps including an entire industry or several, sometimes many, companies and industries, or even society as a whole. These systems are constantly changing: they are created, operated, reorganized and, sometimes, eliminated.

The systems approach is the theoretical and methodological basis of systems analysis.

2. Basic elements of system analysis

2. 1 Conceptual apparatus of system analysis

System analysis is a scientific method for studying complex, multi-level, multi-component systems and processes, based on an integrated approach, taking into account the relationships and interactions between system elements, as well as a set of methods for developing, making and justifying decisions in the design, creation and management of social, economic, human - machine and technical systems.

The term “systems analysis” first appeared in 1948 in the works of the RAND Corporation in connection with the tasks of external management, and became widespread in Russian literature after the translation of S. Optner’s book. Optner S. L., System analysis for solving business and industrial problems, trans. from English, M., 1969;

System analysis is not a set of guidelines or principles for managers, it is a way of thinking in relation to organization and management. System analysis is used in cases where one seeks to study an object from different angles, in a comprehensive manner. The most common area of ​​systems research is considered to be system analysis, which is understood as a methodology for solving complex problems and problems based on concepts developed within the framework of systems theory. Systems analysis is also defined as “the application of systems concepts to management functions associated with planning,” or even to strategic planning and the target planning stage.

The use of systems analysis methods is necessary primarily because in the decision-making process one has to make choices under conditions of uncertainty, which is caused by the presence of factors that cannot be strictly quantified. Procedures and methods of system analysis are aimed specifically at putting forward alternative options for solving a problem, identifying the extent of uncertainty for each option and comparing options according to certain performance criteria. System analysis specialists only prepare or recommend solution options, while decision-making remains within the competence of the relevant official (or body).

The intensive expansion of the scope of use of system analysis is closely related to the spread of the program-target method of management, in which a program is drawn up specifically to solve an important problem, an organization is formed (an institution or a network of institutions) and the necessary material resources are allocated.

A system analysis of the activities of an enterprise or organization is carried out in the early stages of work to create a specific management system.

The ultimate goal of system analysis is the development and implementation of the selected reference model of the control system.

In accordance with the main goal, it is necessary to perform the following systemic studies:

identify general trends in the development of a given enterprise and its place and role in a modern market economy;

establish the features of the functioning of the enterprise and its individual divisions;

identify the conditions that ensure the achievement of the goals;

identify conditions that hinder the achievement of goals;

collect the necessary data for analysis and development of measures to improve the current management system;

use the best practices of other enterprises;

study the necessary information to adapt the selected (synthesized) reference model to the conditions of the enterprise in question.

In the process of system analysis, the following characteristics are found:

the role and place of this enterprise in the industry;

the state of production and economic activity of the enterprise;

production structure of the enterprise;

management system and its organizational structure;

features of the enterprise’s interaction with suppliers, consumers and higher organizations;

innovative needs (possible connections of this enterprise with research and development organizations;

forms and methods of stimulating and remunerating employees.

Thus, system analysis begins with clarifying or formulating the goals of a specific management system (enterprise or company) and searching for a performance criterion that should be expressed in the form of a specific indicator. As a rule, most organizations are multi-purpose. Many goals arise from the peculiarities of the development of the enterprise (company) and its actual state in the period of time under consideration, as well as the state of the environment (geopolitical, economic, social factors). The primary task of system analysis is to determine the global goal of the organization's development and operating goals.

Clearly and competently formulated development goals of an enterprise (company) are the basis for system analysis and development of a research program.

The system analysis program, in turn, includes a list of issues to be studied and their priority:

1. Organizational subsystem analysis, which includes:

policy analysis (tasks);

concept analysis, i.e. systems of views, assessments, ideas for achieving the intended tasks, methods of solution;

analysis of management methods;

analysis of work organization methods;

analysis of structural and functional diagram;

analysis of the personnel selection and placement system;

analysis of information flows;

marketing system analysis;

security system analysis.

2. Analysis of the economic subsystem and diagnostics of problemsdacceptance.

Economic diagnostics of an enterprise - analysis and assessment of the economic performance of an enterprise based on the study of individual results and incomplete information in order to identify possible prospects for its development and the consequences of current management decisions. As a result of the diagnosis, based on an assessment of the state of the farm and its efficiency, conclusions are drawn that are necessary for making quick but important decisions, for example, on targeted lending, on the purchase or sale of an enterprise, on its closure, etc.

Based on analysis and research, a forecast and justification for changing and optimizing the existing organizational and economic subsystem of the enterprise is made.

2. 2 Principles of systems analysis

The most important principles of system analysis boil down to the following: the decision-making process should begin with the identification and clear formulation of final goals; it is necessary to consider the entire problem as a whole, as a single system and identify all the consequences and interrelations of each particular decision; it is necessary to identify and analyze possible alternative ways to achieve the goal; the goals of individual units should not conflict with the goals of the entire program.

System analysis is based on the following principles:
1) unity - joint consideration of the system as a single whole and as a collection of parts;

2) development - taking into account the variability of the system, its ability to develop, accumulate information, taking into account the dynamics of the environment;

3) global goal - responsibility for choosing a global goal. The optimum of subsystems is not the optimum of the entire system;

4) functionality - joint consideration of the structure of the system and functions with priority of functions over structure;

5) decentralization - a combination of decentralization and centralization;

6) hierarchy - taking into account the subordination and ranking of parts;

7) uncertainty - taking into account the probabilistic occurrence of an event;

8) organization - the degree of implementation of decisions and conclusions.

System analysis methodology is developed and applied in cases where decision makers have initial stage there is not enough information about the problem situation to allow choosing a method for its formalized representation, forming a mathematical model, or applying one of the new approaches to modeling that combines qualitative and quantitative techniques. In such conditions, representing objects in the form of systems and organizing the decision-making process using different modeling methods can help.

In order to organize such a process, it is necessary to determine the sequence of stages, recommend methods for completing these stages, and provide for a return to previous stages if necessary. Such a sequence of stages identified and ordered in a certain way with recommended methods or techniques for their implementation is a method of system analysis. System analysis methodology is being developed in order to organize the decision-making process in complex problematic situations. It should focus on the need to justify the completeness of the analysis, the formation of a decision-making model, and adequately reflect the process or object under consideration.

One of the fundamental features of system analysis, which distinguishes it from other areas of systems research, is the development and use of tools that facilitate the formation and comparative analysis of the goals and functions of management systems. Initially, the methods for forming and researching goal structures were based on collecting and summarizing the experience of specialists who accumulated this experience in specific examples. However, in this case it is impossible to take into account the completeness of the data obtained.

Thus, the main feature of systems analysis methods is their combination of formal methods and informal (expert) knowledge. The latter helps to find new ways to solve a problem that are not contained in the formal model, and thus continuously develop the model and the decision-making process, but at the same time be a source of contradictions and paradoxes that are sometimes difficult to resolve. Therefore, research on systems analysis is beginning to rely more and more on the methodology of applied dialectics. Taking into account the above, in the definition of system analysis, it must be emphasized that system analysis:

used to solve problems that cannot be posed and solved by individual methods of mathematics, i.e. problems with the uncertainty of a decision-making situation, when not only formal methods are used, but also methods of qualitative analysis (“formalized common sense”), intuition and experience of decision makers;

combines different methods using a single methodology; is based on a scientific worldview;

unites the knowledge, judgment and intuition of specialists in various fields of knowledge and obliges them to a certain discipline of thinking;

focuses on goals and goal setting.

The characteristics of the scientific directions that have arisen between philosophy and highly specialized disciplines allow us to arrange them approximately in the following order: philosophical and methodological disciplines, systems theory, systems approach, systemology, systems analysis, systems engineering, cybernetics, operations research, special disciplines.

System analysis is located in the middle of this list, since it uses approximately equal proportions of philosophical and methodological concepts (characteristic of philosophy, systems theory) and formalized methods in the model (which is typical of special disciplines).

The scientific directions under consideration have much in common. The need for their use arises in cases where the problem (problem) cannot be solved using the methods of mathematics or highly specialized disciplines. Despite the fact that initially the directions were based on different basic concepts (operations research - from the concept of "operation"; cybernetics - from the concepts of "control", "feedback", "system analysis", systems theory, systems engineering; systemology - from the concept " system"), in the future the directions operate with many of the same concepts - elements, connections, goals and means, structure, etc.

Different directions also use the same mathematical methods. At the same time, there are differences between them that determine their choice in specific decision-making situations. In particular, the main specific features of systems analysis that distinguish it from other systems areas are:

availability of means for organizing the processes of goal setting, structuring and analysis of goals (other system areas pose the task of achieving goals, developing options for achieving them and choosing the best of these options, and system analysis considers objects as systems with active elements, capable and striving for goal setting, and then to achieving the formed goals);

development and use of a methodology that defines the stages, substages of system analysis and methods for their implementation, and the methodology combines both formal methods and models, and methods based on the intuition of specialists, helping to use their knowledge, which makes system analysis particularly attractive for solving economic problems.

System analysis cannot be completely formalized, but some algorithm for its implementation can be chosen. Justification of decisions using system analysis is not always associated with the use of strict formalized methods and procedures; Judgments based on personal experience and intuition are also allowed; it is only necessary that this circumstance be clearly understood.

System analysis can be performed in the following sequence:

1. Statement of the problem is the starting point of the study. In the study of a complex system, it is preceded by work on structuring the problem.

2. Expanding the problem to a problematic, i.e. finding a system of problems significantly related to the problem under study, without which it cannot be solved.

3. Identifying goals: goals indicate the direction in which you need to move in order to solve the problem step by step.

4. Formation of criteria. The criterion is a quantitative reflection of the degree to which the system achieves its goals. A criterion is a rule for selecting a preferred solution from a number of alternatives. There may be several criteria. Multicriteria is a way to increase the adequacy of the description of the goal. The criteria should describe, as far as possible, all important aspects of the goal, but the number of necessary criteria should be minimized.

5. Aggregation of criteria. The identified criteria can be combined either into groups or replaced by a generalizing criterion.

6. Generating alternatives and selecting the best one using criteria. The formation of many alternatives is the creative stage of system analysis.

7. Research of resource opportunities, including information resources.

8. Selection of formalization (models and constraints) to solve the problem.

9. System construction.

10. Use of the results of the conducted systemic research.

2. 3 System analysis methods

The central procedure in system analysis is the construction of a generalized model (or models) that reflects all the factors and relationships of the real situation that may appear in the process of implementing a decision. The resulting model is examined to determine the proximity of the result of applying one or another of the alternative options to the desired one, the comparative costs of resources for each option, and the degree of sensitivity of the model to various undesirable external influences. System analysis is based on a number of applied mathematical disciplines and methods widely used in modern management activities: operations research, the method of expert assessments, the critical path method, queuing theory, etc. The technical basis of system analysis is modern computers and information systems.

Methodological means used in solving problems using system analysis are determined depending on whether a single goal or a certain set of goals is being pursued, whether the decision is made by one person or several, etc. When there is one fairly clearly defined goal, the degree of achievement of which can be assessed based on one criterion; mathematical programming methods are used. If the degree of achievement of a goal must be assessed on the basis of several criteria, the apparatus of utility theory is used, with the help of which the criteria are ordered and the importance of each of them is determined. When the development of events is determined by the interaction of several individuals or systems, each of which pursues its own goals and makes its own decisions, game theory methods are used.

The effectiveness of control systems research is largely determined by the research methods chosen and used. To facilitate the choice of methods in real decision-making conditions, it is necessary to divide the methods into groups, characterize the characteristics of these groups and give recommendations for their use in the development of models and methods of system analysis.

The entire set of research methods can be divided into three large groups: methods based on the use of knowledge and intuition of specialists; methods of formalized representation of control systems (methods of formal modeling of the processes under study) and integrated methods.

As already noted, a specific feature of systems analysis is the combination of qualitative and formal methods. This combination forms the basis of any technique used. Let's consider the main methods aimed at using the intuition and experience of specialists, as well as methods for formalizing systems.

Methods based on identifying and summarizing the opinions of experienced experts, using their experience and non-traditional approaches to analyzing the activities of an organization include: the "Brainstorming" method, the "scenario" type method, the expert assessment method (including SWOT analysis), the "scenario" type method Delphi", methods such as "goal tree", "business game", morphological methods and a number of other methods.

The listed terms characterize one or another approach to enhancing the identification and generalization of the opinions of experienced specialists (the term “expert” translated from Latin means “experienced”). Sometimes all these methods are called "expert". However, there is also a special class of methods related directly to the survey of experts, the so-called method of expert assessments (since in surveys it is customary to give ratings in points and ranks), therefore the above-mentioned and similar approaches are sometimes combined with the term “qualitative” (noting the convention of this name, since when processing opinions received from specialists, they can also be used quantitative methods). This term (albeit somewhat cumbersome) to a greater extent than others reflects the essence of the methods that specialists are forced to resort to when they not only cannot immediately describe the problem under consideration with analytical dependencies, but also do not see which of the methods of formalized representation of systems discussed above Could you help me get a model?

Methods such as "brainstorming". The concept of brainstorming has gained widespread acceptance since the early 1950s as a “method for systematically training creative thinking” aimed at “discovering new ideas and gaining agreement among a group of people based on intuitive thinking.”

Methods of this type have the main goal of searching for new ideas, their wide discussion and constructive criticism. The main hypothesis is that among large number there are at least a few good ideas. Depending on the adopted rules and the rigidity of their implementation, they distinguish between direct brainstorming, the method of exchanging opinions, methods such as commissions, courts (when one group makes as many proposals as possible, and the second tries to criticize them as much as possible), etc. Recently, sometimes brainstorming is carried out in the form of a business game.

When conducting discussions on the issue under study, the following rules apply:

formulate the problem in basic terms, highlighting a single central point;

do not declare any idea false And do not stop exploring any idea;

support an idea of ​​any kind, even if its appropriateness seems doubtful to you at the time;

provide support and encouragement to free discussion participants from inhibitions.

Despite all the apparent simplicity, these discussions give good results.

Methods like "scripts". Methods of preparing and coordinating ideas about a problem or an analyzed object, set out in writing, are called scenarios. Initially, this method involved preparing a text containing a logical sequence of events or possible options solutions to problems unfolded over time. However, later the mandatory requirement of time coordinates was removed, and a script began to be called any document containing an analysis of the problem under consideration and proposals for its solution or for the development of the system, regardless of the form in which it is presented. As a rule, in practice, proposals for the preparation of such documents are first written by experts individually, and then an agreed text is formed.

The scenario provides not only meaningful reasoning that helps not to miss details that cannot be taken into account in the formal model (this is, in fact, the main role of the scenario), but also contains, as a rule, the results of quantitative technical-economic or statistical analysis with preliminary conclusions. The group of experts preparing the scenario usually enjoys the right to obtain the necessary certificates from enterprises and organizations and the necessary consultations.

The role of system analysis specialists in preparing the scenario is to help the involved leading specialists in the relevant fields of knowledge to identify general patterns of the system; analyze external and internal factors influencing its development and formation of goals; identify the sources of these factors; analyze the statements of leading experts in periodicals, scientific publications and other sources of scientific and technical information; create auxiliary information funds (preferably automated) that contribute to solving the corresponding problem.

Recently, the concept of a scenario has been increasingly expanding in the direction of both areas of application and forms of representation and methods of their development: quantitative parameters are introduced into the scenario and their interdependencies are established, methods for preparing a scenario using computers (machine scenarios), methods for targeted management of scenario preparation are proposed .

The script allows you to create a preliminary idea of ​​the problem (system) in situations where it is not possible to immediately display it formal model. But still, a script is a text with all the ensuing consequences (synonymy, homonymy, paradoxes) associated with the possibility of its ambiguous interpretation by different specialists. Therefore, such text should be considered as a basis for developing a more formalized idea of ​​​​the future system or problem being solved.

Methods of expert assessments. The basis of these methods is various forms of expert questioning followed by evaluation and selection of the most preferable option. The possibility of using expert assessments and the justification for their objectivity is based on the fact that the unknown characteristic of the phenomenon under study is interpreted as random value, a reflection of the distribution law of which is the expert’s individual assessment of the reliability and significance of a particular event.

It is assumed that the true value of the characteristic under study is within the range of estimates obtained from a group of experts and that the generalized collective opinion is reliable. The most controversial point in these methods is the establishment of weighting coefficients based on the estimates expressed by experts and the reduction of conflicting estimates to a certain average value.

An expert survey is not a one-time procedure. This method of obtaining information about a complex problem characterized by a large degree of uncertainty should become a kind of “mechanism” in a complex system, i.e. it is necessary to create a regular system of work with experts.

One of the varieties of the expert method is the method of studying the strengths and weaknesses of an organization, opportunities and threats to its activities - the SWOT analysis method.

This group of methods is widely used in socio-economic research.

Methods like "Delphi". Initially, the Delphi method was proposed as one of the procedures for conducting a brainstorming session and should help reduce the influence of psychological factors and increase the objectivity of expert assessments. Then the method began to be used independently. Its basis is feedback, familiarizing experts with the results of the previous round and taking these results into account when assessing the importance of experts.

In specific techniques that implement the Delphi procedure, this tool is used to varying degrees. Thus, in a simplified form, a sequence of iterative brainstorming cycles is organized. In a more complex version, a program of sequential individual surveys is developed using questionnaires that exclude contacts between experts, but provide for familiarizing them with each other’s opinions between rounds. Questionnaires may be updated from round to round. To reduce factors such as suggestion or adaptation to the opinion of the majority, experts are sometimes required to justify their point of view, but this does not always lead to the desired result, but on the contrary, can enhance the effect of adaptation. In the most developed methods, experts are assigned weighting coefficients of the significance of their opinions, calculated on the basis of previous surveys, refined from round to round and taken into account when obtaining generalized assessment results.

Methods like "goal tree". The term “tree” implies the use of a hierarchical structure obtained by dividing the overall goal into subgoals, and these, in turn, into more detailed components, which can be called subgoals of lower levels or, starting from a certain level, functions.

The “goal tree” method is focused on obtaining a relatively stable structure of goals, problems, directions, i.e. a structure that has changed little over a period of time with the inevitable changes that occur in any developing system.

To achieve this, when constructing the initial version of the structure, one should take into account the patterns of goal setting and use the principles of the formation of hierarchical structures.

Morphological methods. The main idea of ​​the morphological approach is to systematically find all possible solutions to a problem by combining selected elements or their features. In a systematic form, the method of morphological analysis was first proposed by the Swiss astronomer F. Zwicky and is often called the “Zwicky method”.

F. Zwicky considers the starting points of morphological research to be:

1) equal interest in all objects of morphological modeling;

2) the elimination of all restrictions and estimates until the complete structure of the study area is obtained;

3) the most accurate formulation of the problem posed.

There are three main schemes of the method:

a method of systematically covering the field, based on identifying the so-called strongholds of knowledge in the area under study and using some formulated principles of thinking to fill the field;

the method of negation and construction, which consists in formulating certain assumptions and replacing them with the opposite ones, followed by analysis of the inconsistencies that arise;

the morphological box method, which consists of determining all possible parameters on which the solution to the problem may depend. The identified parameters form matrices containing all possible combinations of parameters, one from each row, followed by selection of the best combination.

Business games- the simulation method has been developed for making management decisions in different situations by playing according to given rules between a group of people or a person and a computer. Business games allow, with the help of modeling and simulation of processes, to analyze, solve complex practical problems, ensure the formation of a mental culture, management, communication skills, decision-making, and the instrumental expansion of management skills.

Business games act as a means of analyzing management systems and training specialists.

To describe management systems in practice, a number of formalized methods are used, which to varying degrees provide the study of the functioning of systems over time, the study of management schemes, the composition of units, their subordination, etc., in order to create normal operating conditions for the management apparatus, personalization and clear information ensuring management

One of the most complete classifications, based on a formalized representation of systems, i.e. on a mathematical basis, includes the following methods:

- analytical (methods of both classical mathematics and mathematical programming);

- statistical (mathematical statistics, probability theory, queuing theory);

- set-theoretic, logical, linguistic, semiotic (considered as branches of discrete mathematics);

graphic (graph theory, etc.).

The class of poorly organized systems corresponds in this classification to statistical representations. For the class of self-organizing systems, the most suitable models are discrete mathematics and graphical models, as well as their combinations.

Applied classifications are focused on economic and mathematical methods and models and are mainly determined by the functional set of problems solved by the system.

Conclusion

Despite the fact that the range of modeling and problem solving methods used in system analysis is constantly expanding, system analysis is not identical in nature to scientific research: it is not related to the tasks of obtaining scientific knowledge in the proper sense, but is only the application of scientific methods to solving practical problems. management problems and pursues the goal of rationalizing the decision-making process, without excluding from this process the inevitable subjective aspects in it.

Due to the extremely large number of components (elements, subsystems, blocks, connections, etc.) that make up socio-economic, human-machine, etc. systems, system analysis requires the use of modern computer technology - both for building generalized models of such systems, and for operating with them (for example, by playing scenarios for the functioning of systems on such models and interpreting the results obtained).

When conducting system analysis, the team of performers becomes important. The systems analysis team should include:

* specialists in the field of systems analysis - group leaders and future project managers;

* production organization engineers;

* economists specializing in the field of economic analysis, as well as researchers of organizational structures and document flow;

* specialists in the use of technical means and computer equipment;

* psychologists and sociologists.

An important feature of system analysis is the unity of the formalized and informal research tools and methods used in it.

System analysis is widely used in marketing research, since it allows us to consider any market situation as an object for study with a wide range of internal and external cause-and-effect relationships.

Literature

Golubkov 3.P. The use of system analysis in decision making - M.: Economics, 1982

Ignatieva A. V., Maksimtsov M. M. RESEARCH OF CONTROL SYSTEMS, M.: UNITY-DANA, 2000

Kuzmin V. P. Historical background and epistemological foundations
systematic approach. - Psychologist. zhurn., 1982, vol. 3, no. 3, p. 3 - 14; No. 4, p. 3 - 13.

Remennikov V.B. Development of a management solution. Textbook allowance. -- M.: UNITY-DANA, 2000.

Dictionary-reference book for managers./Ed. M.G. Paws. - M.: INFRA, 1996.

Enterprise director's directory. /Ed. M.G. La empty. - M.: INFRA, 1998.

Smolkin A.M. Management: basics of organization. - M.: INFRA-M, 1999.

8. Organizational management. /Ed. A.G. Porshneva, Z.P. Rumyantseva, N.A. Salomatina. --M.: INFRA-M, 1999.

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