Principles and methods of systems analysis. Systematic analysis of legal norms
System analysis - this is a set of studies aimed at identifying general trends and factors in the development of the organization and developing measures to improve the management system and all production economic activity of the organization.
System analysis has the following Features:
It is used to solve problems that cannot be posed and solved by separate methods of mathematics, i.e. problems with the uncertainty of the decision-making situation;
Uses not only formal methods, but also methods of qualitative analysis, i.e. methods aimed at activating the use of intuition and experience of specialists;
Combines different methods using a single methodology;
It is based on the scientific worldview, in particular, on dialectical logic;
Makes it possible to combine knowledge, judgment and intuition of specialists in various fields of knowledge and obliges them to a certain discipline of thinking;
The main attention is paid to goals and purpose.
Application areas System analysis can be determined from the point of view of the nature of the tasks being solved:
Tasks related to the transformation and analysis of goals and functions;
Tasks of developing or improving structures;
Design tasks.
All these tasks are implemented in different ways at different levels of economic management. Therefore, it is advisable to highlight the areas of application of system analysis and according to this principle: tasks of the general public, national economic level; tasks at the industry level; tasks of a regional nature; tasks at the level of associations and enterprises.
10. Stages of the development process and basic methods of adoption management decisions.
Decision making is the process of a rapid course of action among two or more alternatives. Solution is a conscious choice of behavior characteristics in a specific situation.
All solutions can be divided into programmable And non-programmable. Thus, establishing the amount of wages in budgetary organization is a programmable solution that is determined by the laws and regulations in force in the Russian Federation.
By degree of urgency highlight:
research solutions;
crisis-instructional.
Research decisions are made when there is time to obtain additional information. Crisis-intuitive solutions are used when there is a danger that requires an immediate response.
The following are distinguished: decision making approaches:
by degree of centralization;
by degree of individuality;
by employee engagement level.
A centralized approach means that as many decisions as possible should be made at the top level of the organization. The decentralized approach encourages managers to delegate decision-making responsibilities to lower levels of management. In addition, the decision can be made individually or as a group.
As technological processes become more complex, more and more decisions are made by a group consisting of specialists in various fields of scientific knowledge. The degree of employee participation in solving a problem depends on the level of competence. It should be noted that modern management encourages employee participation in solving problems, for example, through the creation of a system for collecting suggestions about improving the operation of the enterprise.
The solution planning process can be divided into six stages: - defining the problem;
Setting goals; developing alternative solutions; choosing an alternative; implementing a solution;
evaluation of results.
The problem usually lies in some deviations from the expected course of events. Next, it is necessary to determine the scale of the problem, for example, what is the proportion of rejected products in the total volume. It is much more difficult to determine the causes of the problem, for example, in which area the technology violation led to the appearance of defects. Defining the problem is followed by setting goals that will serve as the basis for future decisions, such as what the defect rate should be.
The solution to a problem can often be achieved in more than two ways. To form alternative solutions, it is necessary to collect information from many sources. The amount of information collected depends on the availability of funds and the timing of decisions. In an enterprise, as a rule, the probability of achieving results of more than 90% is considered a good indicator.
To select one of the alternatives, it is necessary to consider the correspondence between costs and expected results, as well as the feasibility of implementing the solution in practice and the likelihood of new problems arising after the implementation of the solutions.
Implementation of a decision involves announcing an alternative, issuing the necessary orders, distributing tasks, providing resources, monitoring the process of implementing the decision, and making additional decisions.
After implementing a decision, the manager must evaluate its effectiveness by answering the questions:
Was the goal achieved; was it possible to achieve the required level of expenditure;
Have there been any undesirable consequences?
What is the opinion of employees, managers, and other categories of persons involved in the activities of the enterprise about the effectiveness of the decision.
11. Target approach to management. Concept and classification of goals.
The fundamental principle of management is the correct choice of goal, since purposefulness is the main feature of any human activity. The transition to market relations convincingly shows that managing the process of labor and production is increasingly becoming a process of managing people.
Target represents a specification of the organization’s mission in a form accessible to manage the process of their implementation
Requirements for the goals of the organization:
Functionality for so that managers at various levels can easily transform common goals that are set at a higher level into tasks for lower levels
Establishing a mandatory time connection between long-term and short-term goals
Their periodic review, based on analysis based on specific criteria, to ensure that internal capabilities correspond to existing conditions;
Ensuring the necessary concentration of resources and efforts;
The need to develop a system of goals, and not just one goal;
Coverage of all areas and levels of activity.
Any goal will be effective if it has the following characteristics:
Specific and measurable;
Certainty in time;
Targeting, focus;
Coordination and consistency with other goals and resource capabilities of the organization;
Controllability.
The whole system organization goals must be an interconnected system. This relationship is achieved by linking them using the construction "goal tree". The essence of the concept of a “tree of goals” is that at the first stage of goal setting in an organization, the main goal of its activities is determined. Then one goal breaks down into a system of goals for all spheres and levels of management and production. The number of levels of decomposition (dividing the overall goal into subgoals) depends on the scale and complexity of the goals set, the structure adopted in the organization, and the degree of hierarchy in the structure of its management. At the very top of this model is the overall goal (mission) of the organization, and the foundation is tasks, which are the formulation of work that can be completed in the required manner and within a predetermined time frame.
Directions for improving goal setting in an organization:
Development and specification of parameters of economic analysis in the organization; analysis of the economic activity of the organization;
Control and management of changes in the economic parameters of the organization’s development;
Availability of forecast economic calculations for the development of new markets;
Determining the economic strategy of the organization in relation to competitors, partners and consumers;
Assessment of fixed assets, working capital, labor productivity;
Economic calculations of the population's needs for the proposed organization of goods, services;
Determining a strategic approach to the economic calculation of the base price for a product (service);
Establishing an effective system of remuneration for the organization’s personnel.
Plays an important role in the goal-setting process motivetion. The model for forming a system of organizational goals is built on the basis of a system of motivations that are used at different levels of company management. Effective motivation can be carried out on the basis of a system of means, and not with the help of any one, even very important incentive. Therefore, when developing the goals of an organization, the correct construction and method of applying the motivation system are of great importance.
Classification of organizational goals.
Organizational goals set the parameters of the organization. The goals of an organization are often defined as the directions in which its activities should be conducted. The main goals of the organization are developed by managers of basic resources (professional managers) based on a value system. The top management of the organization is one of the key resources, therefore the value system of the top management influences the structure of the organization's goals, while the integration of the values of the company's employees and shareholders is achieved.
You can select system of organizational goals:
Survival in a competitive environment;
Prevention of bankruptcy and major financial failures;
Leadership in the fight against competitors;
Maximizing “price” or creating an image;
Growth of economic potential;
Increase in production and sales volumes;
Profit maximization;
Minimizing costs;
Profitability.
The goals of the organization are classified:
2. establishment period: strategic, tactical, operational;
3 priorities: especially priority, priority, others;
4measurability: quantitative and qualitative;
5nature of interests: external and internal;
6repetition: constantly recurring and one-time;
7time period: short-term, medium-term, long-term;
8functional orientation: financial, innovative, marketing, production, administrative;
9 stages of the life cycle: at the design and creation stage, at the growth stage, at the maturity stage, at the end of the life cycle stage;
11hierarchies: goals of the entire organization, goals of individual units (projects), personal goals of the employee;
12 scales: company-wide, intra-company, group, individual.
The diversity of the organization’s goals is explained by the fact that the content of the organization’s elements is multidirectional along many parameters. This circumstance determines the need for multiple goals, varying in level of management, management tasks, etc. The classification of goals allows us to better understand the versatility of the activities of business organizations. The criteria used for classification can also be applied by many business organizations. However, the specific expressions of goals within a given classification will remain different. Classification of organizational goals allows you to increase management efficiency by selecting the necessary information and setting methods for each system goal.
- Translation
System analysis provides a rigorous approach to decision-making techniques. It is used to explore alternatives and includes modeling and simulation, cost analysis, technical risk analysis and efficiency analysis.
Unlike SWEBoK, SEBoK is much less common in Russia. At least when preparing the course for the master's degree, I was unable to find any translations of his articles. Nevertheless, the book structures very useful and so far scattered knowledge in the field of development of large systems and, including, systems analysis.
Since my course dealt specifically with system analysis, under the cut there will be a translation of this SEBoK chapter... But these are just a few chapters of one of the 7 sections of the book.
P.S. I would be grateful for your comments and your opinion about this article (quality, necessity) and about your interest in systems analysis and systems engineering.
Basic principles of systems analysis
One of the main tasks of systems engineering is to evaluate the results obtained from its processes. Comparison and assessment are the central object of system analysis, providing the necessary techniques and tools for:- Definition of comparison criteria based on system requirements;
- Assessments of the expected properties of each alternative solution in comparison with the selected criteria;
- A summary assessment of each option and its explanation;
- Selecting the most suitable solution.
The process of analyzing and choosing between alternative solutions to an identified problem/opportunity is described in Section 2 of SEBoK (chapter Systems Approach in Systems Design). Let us define the basic principles of system analysis:
- System analysis is an iterative process consisting of evaluating alternative solutions obtained in the process of system synthesis.
- Systems analysis is based on evaluation criteria based on a description of the problem or opportunity of the system;
- The criteria are based on the basis of an ideal description of the system;
- The criteria must take into account the required behavior and properties of the system in the final solution, in all possible broader contexts;
- The criteria should include non-functional issues, for example: system safety and security, etc. (described in more detail in the chapter “Systems Engineering and Special Design”).
- An "ideal" system may support a "loose" description from which "fuzzy" criteria can be determined. For example, stakeholders are for or against certain types of decisions, relevant social, political or cultural conventions must also be taken into account, etc.
- Comparison criteria should include, at a minimum, cost and time constraints that are acceptable to stakeholders.
- Systems analysis provides a separate trade-off exploration mechanism for analyzing alternative solutions
- Trade-off exploration is an interdisciplinary approach to finding the most balanced solution among many perceived viable options.
- The study considers the entire set of evaluation criteria, taking into account their limitations and relationships. A “system of evaluation criteria” is being created.
- When comparing alternatives, you will have to deal with both objective and subjective criteria. Particular care must be taken to determine the impact of each criterion on the overall score (sensitivity of the overall score).
Exploring trade-offs
Note: In our literature, the term “Analysis of Alternatives” or “Assessment of Alternatives” is more often used.In the context of a system description, a trade-off study consists of comparing the characteristics of each system element and each system architecture option to determine the solution that is overall best suited to the criteria being evaluated. The analysis of various characteristics is carried out in the processes of cost analysis, risk analysis, and efficiency analysis. From a systems engineering perspective, these three processes will be discussed in more detail.
All analysis methods must use general rules:
- Evaluation criteria are used for classification various options solutions. They can be relative or absolute. For example, the maximum price per unit of production is in rubles, cost reduction is %, efficiency increase is %, risk reduction is also in %.
- The acceptable boundaries of the evaluation criteria that are applied during the analysis are determined (for example, the type of costs that need to be taken into account; acceptable technical risks, etc.);
- For comparison quantitative characteristics rating scales are used. Their description should include the maximum and minimum limits, as well as the order in which the characteristics change within these limits (linear, logarithmic, etc.).
- An evaluation score is assigned to each solution option based on all criteria. The purpose of the trade-off study is to provide a quantitative comparison along three dimensions (and their decomposition into separate criteria) for each decision option: cost, risk and effectiveness. This operation is usually complex and requires the creation of models.
- Optimizing characteristics or properties improves the evaluation of the most interesting solutions.
- Subjective evaluation criteria – personal opinion of the analyst. For example, if a component must be beautiful, then what is the criterion of “beautiful”?
- Undefined data. For example, inflation must be taken into account when calculating maintenance costs for the full life cycle of the system. How can a systems engineer predict how inflation will develop over the next five years?
- Sensitivity analysis. The overall score given to each alternative solution is not absolute; Therefore, it is recommended to conduct a sensitivity analysis that takes into account small changes in the “weights” of each evaluation criterion. An estimate is considered reliable if changing the “weights” does not significantly change the estimate itself.
A careful study of the trade-offs determines the acceptable values of the results.
Performance Analysis
Performance analysis is based on the context of use of the system or problem.The effectiveness of the solution is determined based on the implementation of the basic and additional functions systems that are identified based on meeting the requirements of stakeholders. For products, this will be a set of general non-functional qualities, for example: safety, security, reliability, maintainability, ease of use, etc. These criteria are often precisely described in related technical disciplines and fields. For services or organizations, the criteria may be more related to identifying user needs or organizational goals. Typical characteristics of such systems include stability, flexibility, development, etc.
In addition to assessing the absolute effectiveness of a solution, cost and implementation time constraints must also be considered. In general, the role of systems analysis is to identify solutions that can provide efficiency to some extent, taking into account the costs and time allocated for each given iteration.
If none of the solutions can provide a level of effectiveness that justifies the proposed investment, then it is necessary to return to the original state of the problem. If at least one of the options shows sufficient effectiveness, then the selection can be made.
The effectiveness of a solution includes several essential characteristics (but is not limited to): performance, usability, reliability, production, service and support, etc. Analysis in each of these areas highlights the proposed solutions from different perspectives.
It is important to establish a classification of the importance of aspects for efficiency analysis, the so-called. key performance indicators. The main difficulty of efficiency analysis is to correctly sort and select a set of aspects in terms of which efficiency is assessed. For example, if the product is manufactured for one-time use, repairability will not be an appropriate criterion.
Cost Analysis
Cost analysis looks at full life cycle costs. The basic set of typical costs may vary for a specific project and system. The cost structure may include both labor costs (for labor costs) and non-labor costs.| Type | Description and example |
|---|---|
| Development | Design, development of tools (equipment and software), project management, testing, layout and prototyping, training, etc. |
| Manufacturing a product or providing a service | Raw materials and supplies, spare parts and warehouse stock, resources necessary for work (water, electricity, etc.), risks, evacuation, processing and storage of waste or defects, administrative costs (taxes, administration, paperwork, quality control, cleaning , control, etc.), packaging and storage, necessary documentation. |
| Sales and after-sales service | Costs for the sales network (branches, stores, service centers, distributors, obtaining information, etc.), handling complaints and providing guarantees, etc. |
| Customer use | Taxes, installation (at the customer), resources necessary for work (water, fuel, etc.), financial risks etc. |
| Supplies | Transportation and delivery |
| Service | Service centers and visits, prevention, control, spare parts, warranty costs, etc. |
| Removal | Collapsing, dismantling, transport, waste disposal, etc. |
Methods for determining cost costs are described in the “Planning” section (Section 3).
Technical Risk Analysis
Risk is the potential failure to achieve goals within specified cost, schedule, and technical constraints. Consists of two parts:- Probability of implementation (the probability that the risk will be justified and the goals will not be achieved);
- The degree of impact or consequences of implementation.
Risk analysis in any area is based on three factors:
- Analysis of the presence of potential threats or undesirable events and the likelihood of their occurrence.
- Analysis of the consequences of identified threats and their classification according to the severity scale.
- Reducing the likelihood of threats or the level of their impact to acceptable levels.
- Incorrect assessment of technological capabilities;
- Reassessment of the technical readiness of the system element;
- Accidents due to wear and tear or obsolescence of equipment, components or software,
- Dependency on the supplier (incompatible parts, delayed delivery, etc.);
- Human factor (insufficient training, incorrect settings, insufficient error handling, implementation of inappropriate procedures, malicious intent), etc.
Process approach
Purpose and principles of the approach
The systems analysis process is used to:- Ensuring a rigorous approach to decision making, resolving conflicting requirements, and evaluating alternative physical solutions (individual elements and the entire architecture);
- Determining the level of satisfaction of requirements;
- Risk management support;
- Confirmation that decisions are made only after calculating costs, schedules, productivity and the impact of risks on the design or redesign of the system.
System analysis supports other system description processes:
- The processes of describing stakeholder requirements and describing system requirements use systems analysis to resolve conflicts between requirements; in particular those related to costs, technical risks and efficiency. System requirements that are subject to high risks or require significant architectural changes are further discussed.
- The logical and physical architecture development processes use systems analysis to evaluate the characteristics or develop the properties of architecture options, providing rationale for selecting the most effective option in terms of cost, technical risk, and efficiency.
Tasks within the process
Key activities and tasks within this process include:- Planning to explore alternatives:
- Determining the number of alternatives to analyze, the methods and procedures to be used, the expected results (examples of objects to choose from: behavioral scenario, physical architecture, system element, etc.), and justification.
- Creating an analysis schedule according to the availability of models, technical data ( system requirements, description of system properties), personnel qualifications and selected procedures.
- Definition of model selection criteria:
- Selecting evaluation criteria from non-functional requirements (performance, operating conditions, restrictions, etc.) and/or property descriptions.
- Sorting and ordering criteria;
- Defining a comparison scale for each evaluation criterion, and determining the weight of each criterion in accordance with its level of importance relative to other criteria.
- Identifying solution options and associated models and data.
- Evaluation of options using previously defined methods and procedures:
- Perform cost analysis, technical risk analysis, and effectiveness analysis by placing all alternatives on a scale for each evaluation criterion.
- Rate all alternatives on a common rating scale.
- Providing results to the initiating process: evaluation criteria, choice of evaluations, comparison scales, evaluation results for all options, and possible recommendations with justification.
Artifacts and process terminology
As part of the process, artifacts such as:- Model of selection criteria (list, rating scales, weights);
- Reports on analysis of costs, risks, efficiency;
- Report justifying the choice.
The process uses the terms listed in the table below.
| Term | Description |
|---|---|
| Evaluation criterion | In the context of systems analysis, an evaluation criterion is a characteristic used to compare system elements, physical architecture, functional scenarios, and other elements that can be compared. Includes: identifier, name, description, weight. |
| Evaluative choice | Manage system elements based on an evaluation score that explains the selection of system elements, physical architecture, or use case. |
| Evaluation score (score) | The elements of the system, physical architecture, and functional scenarios receive an evaluation score using a set of evaluation criteria. Includes: identifier, title, description, value. |
| Expenses | Value in the selected currency associated with the value of the system element, etc. Includes: identifier, name, description, amount, cost type (development, production, use, maintenance, disposal), valuation method, validity period. |
| Risk | An event that may occur and affect the goals of the system or its individual characteristics (technical risks). Includes: identifier, title, description, status. |
Verifying the correctness of the system analysis
To obtain verified results, it is necessary to ensure that the following points are met:- Correspondence of models and data in the context of system use;
- Compliance of evaluation criteria with respect to the context of use of the system;
- Reproducibility of modeling and calculation results;
- Sufficient level of accuracy of comparison scales;
- Trust in assessments;
- A sufficient level of sensitivity of the obtained scores relative to the weights of the evaluation criteria.
Principles of using models
- Use of general models. Various types of models can be used in the context of systems analysis.
- Physical models are scale models that allow you to experiment with physical phenomena. Specific to each discipline; for example: mock-ups, test benches, prototypes, vibration tables, decompression chambers, air tunnels, etc.
- View models are primarily used to model the behavior of a system. For example, state diagrams, etc.
- Analytical models are used to establish the meaning of estimates. Use equations or diagrams to describe the actual operation of a system. They can be very simple (addition of elements) or incredibly complex (probability distribution with several variables).
- Using the necessary models. At each stage of the project, appropriate models should be used:
- At the beginning of the project are used simple tools, allowing one to obtain rough approximations without much expense or effort. This approximation is often enough to immediately identify unrealistic solutions.
- As the project progresses, it is necessary to improve the accuracy of the data to compare still competing options. The work will be more difficult if the level of innovation in the project is high.
- A systems engineer alone cannot model a complex system; for this, he is assisted by experts from the relevant subject areas.
- Subject matter expert review: when the value of an evaluation criterion cannot be established objectively and accurately. The examination is carried out in 4 stages:
- Selecting respondents to obtain qualified opinions on the issue under consideration.
- Creating a draft questionnaire. Questionnaires with precise questions are easier to evaluate, but if it is too closed, there is a risk of missing important points.
- Conducting interviews with experts on a questionnaire, including conducting an in-depth discussion of the problem to obtain a more accurate opinion.
- Analysis of the results obtained with several different people, comparing their feedback until an agreement on the classification of evaluation criteria or solution options is reached.
The most commonly used analytical models within systems analysis are shown in the table.
The main pitfalls and successful systems analysis practices are described in the two sections below.Model type Description Deterministic (certain) models A model that does not depend on probability theory is called deterministic. - Models based on statistics fall into this category. The principle is to create a model based on a significant amount of data and the results of previous projects. Can only be applied to those system components whose technology is already known.
- Models by analogy also use previous designs. The element being studied is compared with an already existing element with known characteristics. These characteristics are then refined based on the experience of specialists.
- Learning curves allow us to anticipate changes in a feature or technology. One example: “Every time the number of modules produced doubles, the cost of that module decreases by a certain, constant fraction.”
Stochastic (probabilistic) models If the model contains random quantities among the variables, i.e. determined only by some probabilistic characteristics, then the model is called stochastic (probabilistic, random). In this case, all the results obtained when considering the model are stochastic in nature and must be interpreted accordingly.
Probability theory allows you to classify possible decisions as a consequence of many events. These models are applicable to a limited number of events with simple combinations possible options.Multicriteria models If there are more than 10 criteria, it is recommended to use multi-criteria models. They are obtained as a result of the following actions: - Build a hierarchy of criteria;
- Associate each criterion of each branch of the tree with its “weight” relative to the criteria of the same level.
- The weight for each “leaf” of criteria for each branch is calculated by multiplying by all the weights of the branch.
- Evaluate each alternative solution using the criteria sheets, sum up the ratings and compare with each other.
- Using a computer, sensitivity analysis can be performed to obtain an accurate result.
Underwater rocks
Underwater rock Description Analytical modeling is not a decision-making tool The analytical model provides an analytical result from the analyzed data. It should be seen as an aid, but not as a decision-making tool. Models and levels of system decomposition The model can be well adapted to the nth level of system decomposition and is incompatible with a higher level model that uses data from child levels. It is important that the systems engineer ensures that models are consistent across different levels. Optimization is not the sum of optimized elements The overall optimization of the system under study is not the sum of the optimization of each of its parts. Proven Methods
Methodology Description Remain in the operational field Models will never be able to show all the behavior and response of a system: they operate in a limited space with a narrow set of variables. When using a model, it is always necessary to ensure that the input data and parameters are part of the operational field. Otherwise there is a high risk of incorrect results. Develop Models Models must evolve throughout the project: by changing parameter settings, introducing new data (changes in evaluation criteria, functions performed, requirements, etc.), and by using new tools when the previous ones reach the limit of their capabilities. Use multiple model types It is recommended that several different types of models be used simultaneously to compare results and take into account other aspects of the system. Keep context elements consistent Simulation results are always obtained within the context of the simulation: the tools used, the assumptions, the input parameters and data, and the range of output values.
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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. The choice of research methods, the integration of various methods when conducting research 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 best way carry out analysis and get the desired results. To successfully carry out the analysis, it is necessary to select a team of specialists who are familiar with the methods economic analysis and organization of production.
- 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.
- Systems approach is one of the most important methodological principles 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 characteristic high degree 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. Important feature The systematic 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 various models of the object into a single whole. 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 arranged on the basis of subordination of elements lower level- elements of the highest level. 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 the internal and external environment of the organization when analyzing. 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 systems approach contributes, as already mentioned, mainly to the development of the correct method of 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.
The method of system analysis is developed and applied in cases where decision makers at the initial stage do not have sufficient information about the problem situation, allowing them to choose a method for its formalized representation, create a mathematical model, or apply one of the new modeling approaches that combine 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 techniques are being developed in order to organize the decision-making process in complex problem 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 of action to the desired one, the comparative costs of resources for each of the options, 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: operations research, expert assessment method, critical path method, queuing theory, etc. The technical basis of system analysis is modern computing machines 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, quantitative methods can also be used). 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 basic hypothesis is the assumption that among a large number of ideas there are at least a few good ones. 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 for preparing and coordinating ideas about a problem or an analyzed object, set out in in writing, are called scenarios. Initially, this method involved the preparation of a text containing a logical sequence of events or possible solutions to a problem unfolded over time. However, later mandatory requirement time coordinates were 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 a text should be considered as a basis for developing a more formalized understanding of 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 a random variable, the 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 - a simulation method 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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The essence and basic principles of the systems approach in the study of organizational management systems. Application of a systematic approach to analyze the product quality management system using the example of the industrial enterprise Bumkar Trading LLP.
course work, added 10/11/2010
Systematic approach to management and its luminaries. Modern idea of a systems approach. The concept of a systems approach, its main features and principles. Differences between traditional and systemic approaches to management. The importance of a systems approach in management.
course work, added 10/21/2008
Difference between a system and a network. The essence of the concept of "emergence". Principles of the systems approach used in building models. Fundamental, phenomenological models. Effective problem solving using systems analysis. Decision making process.
presentation, added 10/14/2013
The essence and principles of system analysis. SWOT analysis of external opportunities and threats, strengths and weaknesses of the enterprise. Identifying problems in an organization using the Ishikawa diagram. Determination of significant qualities of a manager using the hierarchy analysis method.
test, added 10/20/2013
The essence of system analysis, its object, subject, technology, structure, content, principles, characteristics, methods, meaning, classification and sequence. Justification of principles as the initial stage of constructing a methodological concept.
test, added 11/20/2009
The origins of systems theory. The formation of systems thinking and the development of the systems paradigm in the twentieth century. Theoretical foundations of a systematic approach to organizational management and their application in practice. Stages of development of system ideas in management.
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 management activities. The technical basis of system analysis is modern computers and information systems. System analysis widely uses methods of system dynamics, game theory, heuristic programming, simulation modeling, program-targeted control, etc. An important feature of system analysis is the unity of the formalized and informal research tools and 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 of practical application of 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
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:
- Differentiation, when, with an increase in knowledge and the emergence of new problems, special sciences are separated from more general sciences.
- 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:
- the principle of qualitative originality of various forms of motion of matter, def. the need to study certain aspects of the material world;
- 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, relying on the principles of the systems approach and general theory of systems, 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
- systems research
- systems approach
- specific system concepts
- general systems theory (metatheory in relation to specific systems)
- dialectical materialism (philosophical problems of systems research)
- scientific system theories and models (the doctrine of the earth's biosphere; probability theory; cybernetics, etc.)
- technical systems theories and developments—operations research; systems engineering, systems analysis, etc.
- 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:
- well-structured or quantitatively expressed problems that can be mathematically formalized and solved using formal methods;
- unstructured or qualitatively expressed problems that are described only at the content level and are solved using informal procedures;
- 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:
- a goal or series of goals;
- alternatives for achieving goals;
- resources spent on implementing alternatives;
- model or series of models;
- 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
- identifying the problem;
- formulation of the problem;
- solution to the problem;
- unstructured problem (can be solved using heuristic methods);
- methods of expert assessments;
- poorly structured problem;
- systems analysis methods;
- well structured problem;
- operations research methods;
- decision-making;
- implementation of the solution;
- evaluation of the solution.
1.3 Principles for solving well-structured problems
To solve problems of this class, they are widely used mathematical methods AND ABOUT. In operational research, the main stages can be distinguished:
- Identifying competing strategies to achieve a goal.
- Construction mathematical model operations.
- Evaluating the effectiveness of competing strategies.
- 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.
- persistence of the problem
- restrictions
- operational efficiency criterion
- mathematical model of the operation
- model parameters, but some of the parameters are usually unknown, therefore (6)
- forecasting information (i.e. you need to predict a number of parameters)
- competing strategies
- analysis and strategies
- optimal strategy
- approved strategy (simpler, but which also satisfies a number of criteria)
- implementation of the solution
- model adjustment
The criterion for the effectiveness of an operation must satisfy a number of requirements:
- Representativeness, i.e. the criterion should reflect the main, and not the secondary, purpose of the operation.
- Criticality - i.e. the criterion must change when the operation parameters change.
- Uniqueness, since only in this case is it possible to find a rigorous mathematical solution to the optimization problem.
- Taking into account stochasticity, which is usually associated with the random nature of some operation parameters.
- Accounting for uncertainty, which is associated with the lack of any information about certain parameters of operations.
- Taking into account the counteraction that is often caused by a conscious enemy who controls the full parameters of operations.
- 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
- statement of the problem (2 and 4 (limitations) follow);
- efficiency criterion;
- top level tasks
- restrictions (we organize nesting of models);
- communication with top-level models;
- representativeness;
- criticality;
- uniqueness;
- taking into account stochasticity;
- accounting for uncertainty;
- taking into account counteraction (game theory);
- simplicity;
- mandatory restrictions;
- additional restrictions;
- artificial restrictions;
- selection of the main criterion;
- translation of restrictions;
- construction of a generalized criterion;
- assessment of mathematical performance;
- constructing confidence intervals:
- 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:
- definition of chains of examination;
- formation of a group of specialist analysts;
- formation of a group of experts;
- development of examination scenario and procedures;
- collection and analysis of expert information;
- processing of expert information;
- 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:
- the decision being made relates to the future (a plant that does not exist yet)
- there is a wide range of alternatives
- solutions depend on current incomplete technological advances
- decisions made require large investments of resources and contain elements of risk
- Requirements related to cost and time to resolve the problem are not fully defined
- 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:
- the problem should be formulated broadly enough so that nothing essential is missed;
- 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
- formulation of the problem
- rationale for the purpose
- formation of alternatives
- resource research
- building a model
- evaluation of alternatives
- decision making (choosing one solution)
- sensitivity analysis
- verification of source data
- clarification of the final goal
- search for new alternatives
- 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 |
|
|
|
The scientific tools of SA include the following methods:
- scripting method (trying to describe the system)
- goal tree method (there is an ultimate goal, it is divided into subgoals, subgoals into problems, etc., i.e. decomposition into 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
- directives from higher authorities on the goals and objectives of operations (technical processes, forecasting)
- restrictions on resources, degree of independence, etc.
- information processing
- operation
- external conditions (external environment), a) determination; b) stochastic (the computer fails after a random interval t); c) organized opposition
- information about external conditions
- rational decision
- 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:
- Many potential solutions are highlighted.
- From among them, many competing solutions are selected.
- 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
- possible solutions
- competing solutions
- rational decision
- purpose and objectives of the operation
- operation status information
- information about external conditions
- stochastic
- organized opposition
- resource limitation
- limitation on the degree of independence
- additional restrictions and conditions
- legal factors
- economic forces
- sociological factors
- psychological factors
- traditions and more
- 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 different areas and under different names, and in last years formed into a science called “systems 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, finding out its causes, system analysis involves a wide range of means for this purpose, uses the possibilities various sciences and practical areas of activity. Being essentially applied dialectics, system analysis gives great importance methodological aspects of any systemic research. On the other hand, the applied orientation of system analysis leads to the use of all modern means of 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%
- analysts computer systems — 53%
- programmers - 48%
- electronics engineers - 40%
Development of system views
What does the word “system” mean? large system"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 important property 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