home Deposits Economic informatics lecture. Basic concepts of economic informatics Economic information and information resources Types of economic information What economic informatics studies structure

Economic informatics lecture. Basic concepts of economic informatics Economic information and information resources Types of economic information What economic informatics studies structure

Basic concepts economic informatics are:

Information and economic information;

Objective and economic challenge;

Data - These are messages about objects and processes, presented in a structured or unstructured form, on some material medium (paper documents, magnetic disks). In order for data to be processed by a computer, a number of input operations must be performed on them: first, they are considered as the result of observations or measurements, then they are recorded on a tangible medium (paper documents, signals, etc.) and, finally, data is transferred to a computer, where it is structured and stored in the form of databases or other formal means.

In a broad sense information is defined as information about one or another side of the material world and the processes occurring in it. The term “information” most often refers to the substantive aspect of data, as opposed to data (“data” – fact).

From a scientific point of view, information is a measure of eliminating uncertainty regarding the outcome of an event of interest to us. That is, the concept of information is associated with the probability of a particular event occurring.

Information cannot exist on its own, therefore the presence of an object (source) and a subject (receiver) is implied. The object reflects, and the subject perceives information. The material component of the processes of storage, transmission and transformation of information are information carriers, communication channels, transmitters and receivers.

Information, first of all, is distinguished by its subject content; it is one of the main resources for the life of society, but, unlike natural resources its volume does not decrease over time, but rather only increases.

The following are distinguished: properties of information:

1. Reliability and completeness.

Information is reliable if it does not distort the true state of affairs. Information is complete if it is sufficient for understanding and making decisions.

2.Value and relevance.

The value of information depends on what problems are solved with its help. It is important to have up-to-date information when working in the constantly changing conditions of our world.

3.Clarity and understandability.

Information becomes clear and understandable if it is expressed in the language spoken by those to whom the information is intended.

According to the type of human activity, information is divided into scientific, technical, industrial, managerial, economic, social, legal, etc. Each area of human knowledge operates with its own type of information. Economy, economic activity operates with economic information, which includes both general properties of information and properties reflecting its characteristic features arising from its nature.

Economic information– this is information that reflects and serves the processes of production, distribution, exchange and consumption of material goods. Economic information serves as a management tool and at the same time belongs to its elements. In this case, economic information is considered as a type management information

Economic information is characterized by:

· Large volumes.

Quality management economic processes impossible without detailed information about them. Improving management and increasing production volumes is accompanied by an increase in accompanying information flows.

· Cyclicality.

Most production and economic processes are characterized by repeatability of their constituent stages and information reflecting these processes. This property of economic information allows you to reuse a once created program for data processing.

· Variety of sources and consumers.

This property is due to the diversity of production and economic activity of people.

· The share of logical operations during processing.

Logical operations ensure the appropriate ordering of data in arrays (primary, intermediate, constant and variable). A significant place is occupied by such types of work as ordering, distribution, selection, sampling, and association.

Economic information– characterizes production relations in society (economic information about resources, management processes, financial processes). Properties: alpha-digital signs, variable volume and post signs; discreteness, heterogeneity, persistence, reusability, long shelf life, change)

Economic informatics is the science of information systems ah, used for preparing and making decisions in management, economics and business.

Object Economic informatics are information systems that provide solutions to business and organizational problems that arise in economic systems (economic objects). That is, the object of economic informatics is economic information systems, the ultimate goal of which is the effective management of the economic system.

Item: technology and stages of development of systems for automated processing of economic information and justification of the feasibility of such processing, functional analysis of the subject area, algorithmic representation of the problem and its software implementation.

Peculiarities: presentation and reflection in the form of primary and summary documents, repetition of stages of processing information, the predominance of arithms and log operations in the processing process

Analysis and design of business processes. Functional modeling, which describes the sequence of operations of a business process, as well as modeling the data used in it.

Analysis and design of enterprise information systems architecture. Here the modeling apparatus is somewhat broader, along with the modeling of functions and data, it includes engineering methods for analyzing and predicting IS performance, statistical tools, economic analysis etc.

Improving IP management is solved by methods of management theory, including methods of operations research, organization theory, logistics, etc. Project management methods and models are of great importance.

Analysis and improvement economic efficiency IP A variety of economic analysis methods are used. Currently we are talking about neoclassical tools, new institutional economic theory and management theory.

15.Technology. Information Technology. Information processes.

Technology- a set of methods, processes and materials used in any branch of activity, as well as a scientific description of methods of technical production.

Information Technology (information technology, IT)– a wide class of disciplines and areas of activity related to technologies for managing and processing data using computer technology.

Information process - the process of receiving, creating, collecting, processing, accumulating, storing, searching, distributing, and using information.

Encoding (recording to a medium), transmitting a signal over a communication channel, decoding (converting to a receiving code), code processing.

The characteristic features of modern IT are:

Less processing labor, more quality;

the interactive nature of information processing, a wide range of users and the collective nature of working with information and computing resources;

ensuring a unified IT information space, collective work with information and computing resources based on computer networks and telecommunications systems;

support for multimedia (multimedia) IT, paperless technology.

Information technologies can be divided into classes:

1. General purpose IT (working with text documents, calculations in spreadsheets, maintaining databases, working with computer graphics, etc.).

2. Method-oriented IT, ensuring the use of special models and algorithms for solving problems (mathematical apparatus, statistics, project management, etc.).

3. Problem-oriented IT, taking into account the specifics of the subject area and information needs of users.

Information technologies are developing in the following directions: computer technology; means of communication and communications; software; methodology for organizing design work to create IP.

IT development is related to:

progress in the field of data processing hardware (computers, storage media, communications and communication tools, etc.), industrial technologies for the production of computer components;

development of development methods and tools software, methods of storing and retrieving data on computer media;

16. Information society. Informatization of society at the present time. The concept of the information society emerged at the end of the 20th century; it is closely related to the concept of post-industrial society, a new phase in the development of our entire civilization. Distinctive features of the information society: Information/knowledge is the main product of production; increase in employment in the IT, communications and service sectors; complete informatization (Internet, TV), globalization of the information space; growing role of the individual in the management of social and environmental relations, development of digital markets, electronic democracy/state

Project "Information Society" of the Russian Federation: e-government, improving the quality of life of citizens, overcoming the digital divide, security, digital content for museums and archives, development of the ICT market

Informatization is a complex social process associated with significant changes in the lifestyle of the population. It requires serious efforts in many areas, including eliminating computer illiteracy, creating a culture of using new information technologies, etc.

The driving force behind the development of society should be the production of informational, rather than material, products. In the information society, not only production changes, but also the entire way of life, the value system, and the importance of cultural leisure in relation to material values increases. In the information society, intelligence and knowledge are produced and consumed, which leads to an increase in the share of mental labor. A person will need the ability to be creative, and the demand for knowledge is increasing. The material and technological base of society's information will be various types of systems based on computer equipment and computer networks, information technology, and telecommunications.

Informatization of society- organized socio-economic and scientific-technical process of creating optimal conditions for meeting information needs and realizing the rights of citizens, government bodies, local governments, organizations, public associations based on the formation and use of information resources.

The goal of informatization is to improve the quality of life of people by increasing productivity and facilitating their working conditions.

The main criteria for the development of the information society are the following:

Availability of computers; level of development of computer networks Possession of information culture, i.e. knowledge and skills in the field information technologies

Economic informatics(computer science from French. information- information and automatique- automatic; literally “the science of automation of information processing”) - the science of information systems used to prepare and make decisions in management, economics and business, as well as the economics of these systems.

Economic informatics is a new discipline that emerged in the second half of the 20th century in connection with the rapid development of computer technology and the growth of its application in economics. In Anglo-Saxon countries, computer science is called computer science (literally “the science of computers”), and economic information science is called information systems (literally “information systems”). Modern economic informatics is, first of all, an applied discipline that systematizes the principles of development and operation of information systems (hereinafter referred to as IS) designed to solve various economic problems. Thus, it is at the intersection of computer science itself and the subject area of organization management for which the specialized systems being created were intended. Even in Anglo-Saxon countries, such specialized applied knowledge is in some cases called “computer science”, in particular, there are bioinformatics and military informatics.

Economic computer science also has a common area with economic theory. This general field is the economics of information, a discipline that studies the economic patterns of information creation and dissemination in markets and organizations. In economic computer science, it allows us to describe the value of information and the impact of markets for information goods on the value of IP.

Object and subject of economic informatics

The core of economic informatics includes, first of all, applied knowledge necessary for building IS in the economy and management of organizations in any field - business, non-profit structures and government bodies. In economic informatics, IP is understood as a system designed for collecting, transmitting, processing, storing and issuing information to consumers using computing and communications equipment, software and service personnel.

Influence information systems on the economics of organizations that implement and use them, is described in terms business processes. Implementation information systems creates new IT services, which, in turn, change parameters business processes organizations, their productivity, quality and sustainability. As a result, if implementation is successful, the organization's current profitability and/or long-term competitiveness increases. Therefore, studying business processes commercial and non-profit organizations is one of the main areas of research in economic informatics. These studies include studying the components business process, its quantitative and qualitative characteristics, the IT services it uses, the connection of the business process and its results with the structure of the organization, etc. As a result of these studies, several problems are solved at once:

Along with business processes, economic informatics studies the components of the IS itself: information technology, applications and management. Information technology - technological infrastructure that ensures implementation information processes. It includes all types of computer and telecommunications equipment, system software that controls the operation of the latter, and instrumental environments that support the operation of applications. Information technologies are considered in economic informatics as a means of improving business processes and overcoming their limitations. At the same time, the introduction of information technology does not automatically lead to improvement of business processes; for this it must be combined with the implementation of applications, changes in business processes themselves, advanced training of enterprise employees and improved management information systems. An important part of information technology is platforms - software systems that allow the development of applications.

Applications are specialized programs that directly support certain IT services as part of business processes. Applications can be separate products (business applications) or be part of certain integrated management systems (functional subsystems). Currently, applications have been developed for all areas of enterprise operations and management - procurement, production, marketing and sales, maintenance, personnel management, technological development, finance, accounting etc. The diversity and complexity of modern applications has made it difficult for them to work together within the same enterprise.

For a long time, this problem was solved by creating large monolithic application packages that included the above applications as functional subsystems. Nowadays, the development of integration tools, based primarily on the SOA architecture, has led to the opposite trend, the development of more narrowly focused applications focused on specific subject areas.

For example, SAP, the world's largest manufacturer of business software, currently releases a package of applications SAP Business Suite, which includes the ERP system SAP ERP, CRM system SAP CRM, product lifecycle management system SAP PLM, supply chain management system SAP SCM and supplier relationship management system SAP SRM. It should be emphasized that all of the above are different applications integrated through SOA services. To support SOA services, SAP has created its own integration platform, SAP NetWeaver. Other market leaders have integration platforms similar in purpose - Oracle Fusion Middleware from Oracle, IBM WebSphere from IBM, etc. Each of these platforms can work not only with the manufacturer's applications, but also with applications from other companies, which increases the flexibility of the created systems.

Finally, information systems management ensures coordination among all other IS components, as well as coordination of the development of information systems with business requirements. Enterprise information systems management includes personnel, user, quality, financial and security management, as well as operational management and IS development management. Thus, management turns out to be an extremely important component of the IS, and its improvement, corresponding to the improvement of applications and their technological foundation, is a condition for the balanced development of the system as a whole. According to modern ideas, IS management is, first of all, IT service management.

A separate task is the analysis and design of the architecture of enterprise information systems. Here the modeling apparatus is somewhat broader, along with modeling functions and data, it includes engineering methods for analyzing and predicting IS performance, statistical tools, economic analysis, etc. A special problem is the integration of IS architecture with business architecture and organizational architecture, which is solved by methods of management theory.

The problem of improving IS management is solved by methods of management theory, including methods of operations research, organization theory, logistics, etc. Project management methods and models are of great importance. Recently, the role of project control methods that ensure the achievement of the planned economic effect during the implementation of IS has been growing.

To solve the problem of analyzing and improving the economic efficiency of information systems, various methods of economic analysis are used. Currently we are talking about neoclassical tools, new institutional economic theory and management theory. Each approach uses a variety of techniques, described in the category Economic theory. These same classes of methods are used in the economic analysis of information and markets for information goods.

Short story

Although the prehistory of computer science dates back to at least the 19th century, the history of the use of computers in economics began only in the 50s. 20th century. From this moment we will count the history of economic informatics.

In the initial period, in the 50s and 60s, the computer was a rare and expensive resource. Therefore, the first task of economic informatics was to increase the efficiency of computer use. The first steps on this path were the creation of an operating system - a software package that organizes and maintains the computing process on a computer, and high-level programming languages, as well as compilers from these languages. Already at this stage it became clear that economic objectives, in contrast, for example, scientific problems require much simpler computational algorithms, but they require means of processing large volumes of data with a complex structure. As a result, the COBOL language was developed, supporting complex hierarchical data structures. A further development of this approach was the development of specialized platforms that made it possible to create and maintain increasingly complex databases. These platforms are called database management systems (DBMS).

In the 70s and 80s, the next period in the history of economic informatics began, characterized by the growing penetration of computers into business. At the same time, the computers themselves and their infrastructure became more complex and diverse. New classes of computers have appeared - mini-computers and personal computers (PCs), local and global computer networks, new classes of software. As a result, computers no longer automated individual labor-intensive tasks, but entire functions of the enterprise, including such important ones as production and purchasing planning, accounting and management accounting, design work, etc. For these purposes, new classes of applications were developed - MRP and , later, MRP II, the first integrated production management systems, project management systems, etc. This, in turn, required a means of documenting the relevant business functions and describing the data used in them. The result was the first standards of the IDEF family, including the IDEF 0 function description standard, the IDEF 1X data modeling standard, and several others.

During these same years, economic computer science first encountered the so-called “productivity paradox.” It was that while business and government investments in IT were growing, there were no signs of productivity growth associated with these investments. Nobel laureate R. Solow expressed this problem in clear form: “We see the computer age everywhere except productivity statistics.” Despite the challenge of R. Solow, in the 80s. There was no evidence of a positive impact of IT investment on productivity.

The sharply more complex computing environment of an enterprise, in particular, the explosive growth in the use of personal computers, has caused an accelerated increase in costs for IP. As a result, IT management has increased its focus on cost control. To solve this problem, the Gartner Group developed a TCO model that made it possible to take into account the entire total cost of using IP throughout the entire life cycle of the latter. Although this model was a significant advance in IT cost accounting, it had a number of shortcomings, as a result of which its widespread use in some cases led to incorrect conclusions. The largest of these mistakes was the initiative to develop a network computer specifically designed to reduce the TCO of corporate IP. A number of major PC manufacturers have launched their networked computers onto the market without any success. Interestingly, later, in the 2000s. The ideas of a network computer were again in demand, and this time with much greater success. However, in the 80s. the project turned out to be premature.

90s were marked by two major technical innovations - the transition to the so-called. client-server architecture and the widespread use of the Internet. The new IS architecture meant a transition to distributed applications, one part of which carried out data processing as such and was located on computers specially dedicated for this (servers), and the other ensured the transmission of requests to servers, receiving responses from the latter and presenting the results of requests to the end user (client). It was according to this scheme that e-mail, work with databases, and provision of Internet access were organized.

The Internet became another, even more significant revolution of the 90s. It should be noted that the Internet infrastructure in the form of data networks and global computer networks was created much earlier (the first segments of the ARPAnet network, the predecessor of the Internet, were created back in 1969), the massive use of the Internet by individual users and corporations occurred precisely in the 90s gg. This was due to the emergence of the “World Wide Web” WWW - a network of hyperlinks that connected arrays of information (“pages”) located both on the same server and on different servers. At the same time, search engines appeared, allowing Internet users to quickly find the necessary information. The new technology was quickly commercialized, first for advertising, then for actual transactions. Already in 1994, the bookselling site Amazon.com appeared, and in 1995, the online auction Ebay. At the same time, in the 90s, the payment and logistics infrastructure for Internet transactions took shape. As a result, a large number of businesses have emerged that exist exclusively on the Internet - the so-called. dot-com. Inflated expectations for such businesses gave rise to the so-called “dot-com bubble” - an unjustified increase in stock prices of Internet companies. This “bubble” ended with the crash of 2000.

The rapid development of technology has posed new challenges for economic informatics. First, the pervasive nature of IT has created a need for an integrated description of the role of IT in business. This description is based on the concepts of business process and value chains. This provided a holistic view of the business process, especially important when changing the latter.

Secondly, a whole series of new classes of applications have emerged that solve newly emerging business management problems. These were, first of all, ERP systems, which became a further development of MRP II systems. In addition to them, customer relationship management (CRM), supplier relationship management (SRM) and supply chain management (SCM) systems were created.

Grown up computing power, as well as data storage capacity, made it possible to create specialized analytical systems that process data in real time (OLAP). Finally, the emergence of electronic business gave rise to a new broad class of systems that mediate electronic transactions - B2B, B2C, etc.

Thirdly, there has been a further complication of the tasks of IT services in enterprises. A standard model of IT service business processes, containing the main tasks of the latter and well-proven approaches to solving them, could provide important assistance in these conditions. Such a model was the ITIL model, the first version of which appeared at the turn of the 80s - 90s. Wide recognition of the model in business and government agencies led to the rapid improvement of the library, and at the turn of the 90s - 2000s. its second version was released, and in 2007 the third. Currently, the ITIL library has become the de facto standard for IP management in Europe. Another response to the increasing complexity of the tasks of the IT service was IS outsourcing - the transfer of all or part of the IS maintenance functions to an external supplier. Outsourcing became a popular solution to IT service problems in the 90s.

Finally, in the 90s. The IT productivity paradox has been resolved. A number of researchers have shown that in the presence of complementary changes in business processes firms' IP investment has a significant positive impact on productivity. At the same time, a significant contribution of investments in IP to the capitalization of the company on the stock market was discovered.

The current stage of IP development has brought new achievements. One of the most important was the SOA business application integration technology, which for the first time made it possible to ensure stable and effective interaction of applications from different suppliers. Perhaps an even more important advancement was the so-called. “cloud computing”, which is the provision of IT services over the Internet, in which the details of the IT infrastructure are hidden from the end users of the service. This eliminates most application compatibility and integration issues. Cloud computing eliminates the specific requirements that a number of IT services place on a customer's IT infrastructure, making IT services as easy to access as power from an electrical outlet. An important factor in the development of IT has also been the widespread use of open source software, which represents not so much a technical innovation as an alternative model of copyright.

In parallel with the development of technology, IP management and economic analysis of the latter developed. In management, the main direction of development has been the deepening of outsourcing, the transition from outsourcing of individual IS support functions to outsourcing of business processes as a whole. Outsourcing also influenced the development of the ITIL model, which in its third version is focused not so much on enterprise IT services, as before, but on outsourcing service providers.

In the economics of IP, one of the most important areas has become the economics of copyright. The development of the market for information goods, on the one hand, sharply expanded the volume of consumption of the latter, on the other hand, it limited the rights of users to consume the latter. The severe restrictions placed on users of information goods have given rise to widespread discussion of the economics of copyright in terms of the balance between incentives for innovation and monopoly rights of producers. This has deepened understanding of the institution of copyright, but has not yet led to practical recommendations in this area.

Open source software has become a real alternative to the institution of copyright in the field of software. The GPL license provides the user with four freedoms: freedom to use the software, freedom to study the software and change the source code, freedom to distribute copies of the software, and freedom to distribute modified software. The main limitation imposed by the GPL is that software obtained under the GPL must continue to be distributed under the terms of the GPL.

Economic informatics developed along a special path in the USSR. The planned economy, on the one hand, created a number of incentives for the introduction of information technologies and systems into the national economy, on the other, it imposed extremely strict restrictions on their use. As a result, the introduction of information technologies and systems into the national economy of the USSR was limited and inconsistent, although it led to a number of major successes.

The first success was the very creation of the computer technology industry in the USSR, which for several decades remained at the level of advanced Western countries. Among the creators of Soviet computer technology, S.A. should be mentioned first of all. Lebedeva, I.S. Bruka, B.I. Rameeva, V.M. Glushkov and G.P. Lopato, who created independent design schools for the development of computers and established their mass production.

The development of computer production has raised the question of their use in the national economy. Already in 1959 A.I. Berg, A.I. Kitov and A.A. Lyapunov in the report “On the possibilities of automation of control national economy» raised the question of the use of computers in economic management. However, the technical capabilities of computers at that time did not allow the large-scale use of computers in planning - the main function of managing the national economy at that time. Serious attempts at such automation were made only in the 70s. in the form of an attempt to create an ACS system (automated control systems) with OGAS (National Automated System for collecting, storing and processing information) at the top level.

Large-scale investments in automated control systems did not bring the expected return. The use of automated control systems encountered problems with the quality of information and turned out to be incompatible with the real economic mechanisms operating in a socialist economy. In shock conditions economic reforms 1990s ACS developers were unable to adapt them to new economic conditions, as a result of which ACS quickly faded away. IN modern Russia Economic informatics has not received significant development, and the existing works are fragmentary.

Structure of economic informatics

In modern economic informatics, the following main directions can be distinguished.

First of all, this is the analysis and modeling of business processes. This is a complex and large-scale activity, taking into account the specifics of industries and countries. An important part of it is the description and analysis of newly emerged business processes and business models. Today, such models are based on the increasing use of IT. A feature of recent decades has been end-to-end business processes, covering a number of interconnected enterprises, united, first of all, through IP.

The complexity and, at the same time, dynamism of modern IS require special attention to the problems of IS architecture. It is the timely and accurate solution of architectural problems that allows us to ensure high quality IT services even in the face of large-scale changes. Economic informatics creates a theoretical and methodological basis for such decisions. Today, several trends can be identified in IS architecture:

Ensuring integration of IT architecture and business and organizational architecture;

Building an organization’s IT architecture based on a network of interconnected service providers that outsource business processes;

Corporate data finds itself at the center of modern IT architecture, especially in conditions of developed outsourcing;

Increasing the flexibility of IT services and ease of access to them by end users, primarily based on cloud computing.

A separate area of economic informatics is the development of IP management. Today, the ITIL model dominates in this area, but the question of the boundaries of its application remains unresolved. An important area of research is also the study of outsourcing, the criteria for its success and ways to achieve it. Finally, in modern conditions Measuring and ensuring the cost-effectiveness of IP is of particular importance, which we will discuss in more detail below.

Although the “productivity paradox” has long been resolved, research into the cost-effectiveness of IS is still an important part of economic computer science. Today, the main directions for increasing the efficiency of information systems have already been outlined, these are solving real business problems using IT, changing business processes aimed at unlocking the potential of IT, and improving staff qualifications. Along with this, IP allows you to change the company's portfolio of products and services, making it more flexible and diversified.

Finally, the increasing focus on purchased IS components and purchased services increases the importance of the market for information goods. The study of this market using economic informatics methods is increasingly important for this science.

Unresolved problems and priority areas

Despite a number of successes, a number of unsolved problems remain in economic informatics today. Here are the most important of them:

What determines the success of IS in an organization? Despite developed recommendations for the development and implementation of information systems, projects for the development and implementation of information systems end in failure in 30-50% of cases, according to various estimates.
How to evaluate the effectiveness of IS in specific situations? Research into the effectiveness of IS has not yet led to the development of practically valuable methods that allow assessing the effectiveness of specific projects in this area.
Are best practices always best practices? A number of studies show that the organizations observed today belong to several different types (in the original author's terminology, configurations). Probably different configurations require different ICs and various approaches to their implementation.
How reasonable is today's copyright law? The restrictions imposed by modern copyright on end users are seen as increasingly onerous, and reasonable alternatives are emerging.

It was in the 19th century that storage of information on punched cards, Charles Babbage’s “Analytical Engine” and, finally, the tabulator, a computing device that processes data stored on punched cards, were invented

Ministry of Education of Ukraine

Kyiv National Economic University

"Economic Informatics"

Introduction.

Man has always made decisions in all areas of his activity. An important area of decision making is related to production. The larger the production volume, the more difficult it is to make a decision and, therefore, the easier it is to make a mistake. A natural question arises: is it possible to use a computer to avoid such errors? The answer to this question is given by a science called cybernetics.

Cybernetics (derived from the Greek “kybernetike” - the art of management) is the science of the general laws of receiving, storing, transmitting and processing information.

The most important branch of cybernetics is economic cybernetics - a science that deals with the application of the ideas and methods of cybernetics to economic systems.

Economic cybernetics uses a set of methods for studying management processes in the economy, including economic and mathematical methods.

Currently, the use of computers in production management has reached a large scale. However, in most cases, computers are used to solve so-called routine tasks, that is, tasks related to the processing of various data, which before the use of computers were solved in the same way, but manually. Another class of problems that can be solved using a computer are decision-making problems. To use a computer for decision making, it is necessary to create a mathematical model.

Human capabilities are quite diverse. If we put them in order, we can distinguish two types: physical and mental. Man is so constructed that what he possesses is not enough for him. And the endless process of increasing its capabilities begins. To lift more, one of the first inventions appears - a lever; to move a load more easily - a wheel. These tools still only use the energy of man himself. Over time, application begins external sources energy: gunpowder, steam, electricity, atomic energy. It is impossible to estimate how much the energy used from external sources exceeds human physical capabilities today. As for the mental abilities of a person, then, as they say, everyone is dissatisfied with his condition, but is satisfied with his mind. Is it possible to make a person smarter than he is? To answer this question, it should be clarified that all human intellectual activity can be divided into formalized and informal.

Formalized activity is an activity that is performed according to certain rules. For example, performing calculations, searching in reference books, and graphic work can undoubtedly be entrusted to a computer. And like everything a computer can do, it does it better, that is, faster and better than a person.

Informalized activity is an activity that occurs using some rules unknown to us. Thinking, consideration, intuition, common sense - we do not yet know what it is, and naturally, all this cannot be entrusted to a computer, if only because we simply do not know what to entrust, what task to assign to the computer.

A type of mental activity is decision making. It is generally accepted that decision making is an informal activity. However, this is not always the case. On the one hand, we don't know how we make decisions. And explaining some words with the help of others like “we make decisions using common sense” does not give anything. On the other hand, a significant number of decision-making problems can be formalized. One type of decision-making problem that can be formalized is optimal decision-making problem, or optimization problem. The optimization problem is solved using mathematical models and the use of computer technology.

Modern computers meet the highest requirements. They are capable of performing millions of operations per second, their memory can contain all the necessary information, and the display-keyboard combination ensures a dialogue between a person and a computer. However, one should not confuse successes in the creation of computers with achievements in the field of their application. In fact, all that a computer can do is, according to a program specified by a person, to ensure the transformation of source data into results. We must clearly understand that the computer does not and cannot make decisions. The decision can only be made by a human leader who is endowed with certain rights for this purpose. But for a competent manager, a computer is an excellent assistant, capable of developing and offering a set of a wide variety of solutions. And from this set, a person will choose the option that, from his point of view, turns out to be more suitable. Of course, not all decision-making problems can be solved using a computer. Nevertheless, even if solving a problem on a computer does not end in complete success, it still turns out to be useful, since it contributes to a deeper understanding of this problem and its more rigorous formulation.

Solution stages.

1. Selecting a task

2. Modeling

3. Drawing up an algorithm

4. Programming

5. Entering initial data

6. Analysis of the obtained solution

In order for a person to make a decision without a computer, he often doesn’t need anything. I thought and decided. A person, good or bad, solves all the problems that arise before him. True, there are no guarantees of correctness in this case. The computer does not make any decisions, but only helps to find solutions. This process consists of the following steps:

1. Selecting a task.

Solving a problem, especially a fairly complex one, is quite a difficult task and requires a lot of time. And if the task is chosen poorly, this can lead to loss of time and disappointment in using a computer for decision making. What basic requirements must the task satisfy?

A. There must be at least one solution to it, because if there are no solution options, then there is nothing to choose from.

B. We must clearly know in what sense the desired solution should be the best, because if we do not know what we want, the computer will not be able to help us choose the best solution.

The choice of a problem ends with its meaningful formulation. It is necessary to clearly formulate the problem in ordinary language, highlight the purpose of the research, indicate the limitations, and pose the main questions to which we want to receive answers as a result of solving the problem.

Here we should highlight the most significant features economic object, the most important dependencies that we want to take into account when building the model. Some hypotheses for the development of the research object are formed, the identified dependencies and relationships are studied. When a problem is selected and its content is formulated, one has to deal with experts in the subject area (engineers, technologists, designers, etc.). These specialists, as a rule, know their subject very well, but do not always have an idea of what is required to solve a problem on a computer. Therefore, a meaningful formulation of a problem often turns out to be oversaturated with information that is completely unnecessary for working on a computer.

2. Modeling

An economic-mathematical model is understood as a mathematical description of the economic object or process under study, in which economic patterns are expressed in abstract form using mathematical relationships.

The basic principles of creating a model come down to the following two concepts:

1. When formulating a problem, it is necessary to cover the phenomenon being modeled quite broadly. Otherwise, the model will not provide a global optimum and will not reflect the essence of the matter. The danger is that optimizing one part may come at the expense of others and to the detriment of the overall organization.

2. The model should be as simple as possible. The model must be such that it can be evaluated, verified and understood, and the results obtained from the model must be clear to both its creator and the decision maker.

In practice, these concepts often conflict, primarily because there is a human element involved in collecting and entering data, checking errors, and interpreting results, which limits the size of the model that can be analyzed satisfactorily. The size of the model is used as a limiting factor, and if we want to increase the breadth of coverage, we have to reduce the detail and vice versa.

Let's introduce the concept of a hierarchy of models, where the breadth of coverage increases and the detail decreases as we move to higher levels of the hierarchy. At higher levels, in turn, restrictions and goals are formed for lower levels.

When building a model, it is also necessary to take into account the time aspect: the planning horizon generally increases with the growth of the hierarchy. While the long-term planning model of an entire corporation may contain few day-to-day, day-to-day details, the production planning model of an individual division consists mainly of such details.

When formulating a problem, the following three aspects must be taken into account:

1. Factors to be Investigated: The objectives of the study are fairly loosely defined and largely depend on what is included in the model. In this regard, it is easier for engineers, since the factors they study are usually standard, and the objective function is expressed in terms of maximum income, minimum costs, or perhaps minimum consumption of some resource. At the same time, sociologists, for example, usually set the goal of "social utility" or the like, and find themselves in the difficult position of having to attribute a certain "utility" to various actions, expressing it in mathematical form.

2. Physical boundaries: The spatial aspects of the study require detailed consideration. If production is concentrated at more than one point, then it is necessary to take into account the corresponding distribution processes in the model. These processes may include warehousing, transportation, and equipment scheduling tasks.

3. Time Limits: The time aspects of the study pose a serious dilemma. Usually the planning horizon is well known, but a choice must be made: either model the system dynamically in order to obtain time schedules, or model static functioning at a certain point in time.

If a dynamic (multi-stage) process is being modeled, then the size of the model increases according to the number of time periods (stages) under consideration. Such models are usually conceptually simple, so the main difficulty lies more in the ability to solve the problem on a computer in an acceptable time than in the ability to interpret a large volume of output data. c It is often sufficient to build a model of the system at a given point in time, for example, at a fixed year, month, day, and then repeat the calculations at certain intervals. In general, the availability of resources in a dynamic model is often estimated approximately and determined by factors beyond the scope of the model. Therefore, it is necessary to carefully analyze whether it is really necessary to know the time dependence of the model characteristics, or whether the same result can be obtained by repeating the static calculations for a number of different fixed moments.

3. Drawing up an algorithm.

An algorithm is a finite set of rules that allow a purely mechanical solution to any specific problem from a certain class of similar problems. This means:

¨ the initial data can change within certain limits: (massiveness of the algorithm)

¨ the process of applying rules to the initial data (the path to solving the problem) is uniquely defined: (determinism of the algorithm)

¨ at each step of the process of applying the rules, it is known what to consider as the result of this process: (the effectiveness of the algorithm)

If the model describes the relationship between the initial data and the desired quantities, then the algorithm is a sequence of actions that must be performed in order to move from the initial data to the desired quantities.

A convenient form of writing an algorithm is a block diagram. It not only quite clearly describes the algorithm, but is also the basis for drawing up a program. Each class of mathematical models has its own solution method, which is implemented in an algorithm. Therefore, it is very important to classify problems according to the type of mathematical model. With this approach, problems of different content can be solved using the same algorithm. Algorithms for decision-making problems are, as a rule, so complex that it is almost impossible to implement them without the use of a computer.

4. Drawing up a program.

The algorithm is written using ordinary mathematical symbols. In order for it to be read by a computer, it is necessary to create a program. A program is a description of an algorithm for solving a problem, specified in a computer language. Algorithms and programs are united by the concept of “mathematical software”. Currently, the cost of software is approximately one and a half times the cost of a computer, and there is a constant further relative increase in the cost of software. Already today, the subject of acquisition is precisely mathematical software, and the computer itself is just a container, packaging for it.

Not every task requires an individual program. Today, powerful modern software tools have been created - application software packages (APP).

PPP is a combination of model, algorithm and program. Often, you can choose a ready-made package for a task that works great and solves many problems, among which you can find ours. With this approach, many problems will be solved quickly enough, because there is no need to engage in programming.

If it is impossible to use the PPP to solve a problem without changing it or the model, then you need to either adjust the model to the PPP input, or modify the PPP input so that the model can be entered into it.

This procedure is called adaptation. If a suitable PPP is in the computer memory, then the user’s job is to enter the necessary required data and obtain the required result.

5. Entering initial data.

Before entering the initial data into the computer, they, of course, need to be collected. Moreover, not all the initial data available in production, as is often attempted, but only those that are included in the mathematical model. Consequently, collecting initial data is not only advisable, but also necessary, only after the mathematical model is known. Having the program and entering the initial data into the computer, we will obtain a solution to the problem.

6. Analysis of the obtained solution

Unfortunately, quite often mathematical modeling is mixed with a one-time solution to a specific problem with initial, often unreliable data. To successfully manage complex objects, it is necessary to constantly rebuild the model on a computer, adjusting the initial data taking into account the changed situation. It is inappropriate to spend time and money on drawing up a mathematical model in order to perform one single calculation on it. An economic-mathematical model is an excellent means of obtaining answers to a wide range of questions that arise during planning, design and production. A computer can become a reliable assistant in making everyday decisions that arise in the course of operational production management.

DESCRIPTIVE LIMITATIONS

These constraints describe the functioning of the system under study. They represent a special group of balance equations related to the characteristics of individual blocks, such as mass, energy, costs. The fact that in a linear programming model the balance equations must be linear excludes the possibility of representing such fundamentally nonlinear dependencies as complex chemical reactions. However, those changes in operating conditions that allow a linear description (at least approximately) can be taken into account in the model. Balance ratios can be entered for some complete part of the flowchart. In static (one-stage) models such relationships can be

present in the form:

Input + output = 0

The dynamic (multistage) process is described by the relations:

Input + output + accumulation = 0,

where savings is understood as net growth for the period under review.

LIMITATIONS ON RESOURCES AND FINAL CONSUMPTION

With these restrictions the situation is quite clear. In the very in simple form resource constraints are upper bounds on variables representing the consumption of resources, and final product consumption constraints are lower bounds on variables representing the production of a product. Resource restrictions are as follows:

A i1 X 1 + ... + A ij X j + ... + A in X n Bi,

where A ij is the consumption of the i-th resource per unit X j, j = 1 ... n, and Bi is the total volume of the available resource.

CONDITIONS IMPOSED EXTERNALLY

DEFINITION OF TARGET FUNCTION

The model's objective function usually consists of the following components:

1) Cost of the product produced.

2) Capital investments in buildings and equipment.

3) Cost of resources.

4) Operating costs and equipment repair costs.

Classification of economic and mathematical models

An important stage in the study of the phenomena of objects of processes is their classification, which acts as a system of subordinate classes of objects, used as a means for establishing connections between these classes of objects. The classification is based on the essential characteristics of objects. Since there can be a lot of signs, the classifications performed can differ significantly from each other. Any classification must pursue the achievement of its goals.

The choice of classification purpose determines the set of characteristics by which objects to be systematized will be classified. The purpose of our classification is to show that optimization problems, completely different in content, can be solved on a computer using several types of existing software.

Here are some examples of classification characteristics:

1 area of use

3. Mathematical model class

The most common optimization problems arising in economics are linear programming problems. Their prevalence is explained by the following:

1) With their help, they solve problems of resource allocation, to which

a very large number of very different tasks are reduced

2) Reliable methods for solving them have been developed and implemented in the supplied software

3) A number of more complex problems are reduced to linear programming problems

Mathematical modeling in management and planning

One of the powerful tools available to people responsible for managing complex systems is modeling. Model is a representation real object, systems or concepts in some form different from the form of their actual real existence. Typically, a model serves as a tool to aid in explanation, understanding, or improvement. Analysis of mathematical models provides managers and other leaders with an effective tool that can be used to predict the behavior of systems and compare the results obtained. Modeling allows you to logically predict the consequences of alternative actions and shows quite confidently which of them should be preferred.

The enterprise has some types of resources, but the total supply of resources is limited. Therefore, an important task arises: choosing the optimal option that ensures achievement of the goal with minimal expenditure of resources. Thus, effective production management implies such an organization of the process in which not only the goal is achieved, but also the extreme (MIN, MAX) value of some efficiency criterion is obtained:

K = F(X1,X2,...,Xn) -> MIN(MAX)

Function K is a mathematical expression of the result of an action aimed at achieving a goal, and therefore it is called the target function.

Functioning of complex production system is always determined by a large number of parameters. To obtain an optimal solution, some of these parameters must be turned to the maximum, and others to the minimum. The question arises: is there even a solution that best satisfies all the requirements at once? We can confidently answer - no. In practice, a solution in which any indicator has a maximum, as a rule, does not turn other indicators into either a maximum or a minimum. Therefore, expressions like: produce products of the highest quality at the lowest cost are simply a solemn phrase and are essentially incorrect. It would be correct to say: to obtain products of the highest quality at the same cost, or to reduce the cost of production without reducing its quality, although such expressions sound less beautiful, but they clearly define the goals. Choosing a goal and formulating a criterion for achieving it, that is, an objective function, represents the most difficult problem of measuring and comparing heterogeneous variables, some of which are in principle incommensurable with each other: for example, safety and cost, or quality and simplicity. But it is precisely such social, ethical and psychological concepts that often act as motivation factors in determining the goal and criterion of optimality. In real production management problems, it is necessary to take into account that some criteria are more important than others. Such criteria can be ranked, that is, their relative importance and priority can be established. In such conditions, the optimal solution must be considered to be one in which the criteria with the highest priority receive maximum values. The limiting case of this approach is the principle of identifying the main criterion. In this case, one criterion is taken as the main one, for example, the strength of steel, the calorie content of the product, etc. Based on this criterion, optimization is carried out; the rest are subject to only one condition: that they be no less than some specified values. It is impossible to carry out ordinary arithmetic operations between ranked parameters; it is only possible to establish their hierarchy of values and a scale of priorities, which is a significant difference from modeling in the natural sciences.

When designing complex technical systems, when managing large-scale production or directing military operations, that is, in situations where it is necessary to make responsible decisions, practical experience is of great importance, making it possible to identify the most significant factors, cover the situation as a whole and choose the optimal path to achieve the goal. . Experience also helps to find similar cases in the past and, if possible, avoid erroneous actions. Experience means not only the decision maker’s own practice, but also other people’s experience, which is described in books, summarized in instructions, recommendations and other guidance materials. Naturally, when the solution has already been tested, that is, it is known which solution best satisfies the set goals, the problem of optimal control does not exist. However, in reality, situations are almost never exactly the same, so decisions and management always have to be made under conditions of incomplete information. In such cases, they try to obtain the missing information using guesswork, assumptions, the results of scientific research, and especially studying using models. A scientifically based control theory is in many ways a set of methods for replenishing missing information about how a control object will behave under the selected influence.

The desire to obtain as much information as possible about controlled objects and processes, including the features of their future behavior, can be satisfied by studying the properties of interest to us on models. A model provides a way to represent a real object, which makes it possible to easily and cost-effectively explore some of its properties. Only the model allows us to study not all properties at once, but only those of them that are most significant for a given consideration. Therefore, models allow you to form a simplified idea of the system and obtain the desired results easier and faster than when studying the system itself. The model of the production system is first of all created in the mind of the employee performing management. Using this model, he mentally tries to imagine all the features of the system itself and the details of its behavior, to anticipate all the difficulties and provide for all the critical situations that may arise in various operating modes. He makes logical conclusions, carries out drawings, plans and calculations. The complexity of modern technical systems and production processes means that different types of models have to be used to study them.

The simplest are scale models in which natural values of all sizes are multiplied by a constant value - the modeling scale. Large objects are represented in a reduced form, and small ones in an enlarged form.

In analogue models, the processes under study are not studied directly, but by analogous phenomena, that is, by processes that have a different physical nature, but which are described by the same mathematical relationships. For such modeling, analogies between mechanical, thermal, hydraulic, electrical and other phenomena are used. For example, the oscillations of a weight on a spring are similar to the fluctuations of current in an electrical circuit, and the movement of a pendulum is similar to the voltage fluctuations at the output of an alternating current generator. The most general method scientific research is the use of mathematical modeling. A mathematical model describes the formal relationship between the values of the parameters at the input of the modeled object or process and the output parameters. In mathematical modeling, one abstracts from the specific physical nature of the object and the processes occurring in it and considers only the transformation of input quantities into output ones. Analyzing mathematical models is easier and faster than experimentally determining the behavior of a real object in various operating modes. In addition, the analysis of the mathematical model allows us to highlight the most essential properties of a given system, to which special attention should be paid when making a decision. An additional advantage is that with mathematical modeling it is not difficult to test the system under study under ideal conditions or, conversely, in extreme conditions, which for real objects or processes are costly or associated with risk.

Depending on what information the manager and his

employees preparing decisions, the decision-making conditions and the mathematical methods used to develop recommendations change.

The complexity of mathematical modeling under conditions of uncertainty depends on the nature of the unknown factors. Based on this criterion, problems are divided into two classes.

1) Stochastic problems, when unknown factors are random variables for which the laws of probability distribution and other statistical characteristics are known.

2) Uncertain problems, when unknown factors cannot be described by statistical methods.

Here is an example of a stochastic problem:

We decided to organize a cafe. We don’t know how many visitors will come to it per day. It is also unknown how long service will continue for each visitor. However, the characteristics of these random variables can be obtained statistically. An efficiency indicator that depends on random variables will also be a random variable.

In this case, as an indicator of efficiency, we take not the random variable itself, but its average value and choose such a solution when

at which this average value becomes a maximum or a minimum.

Conclusion.

Computer science plays an important role in modern economic science, which led to the identification of a separate direction in the development of science - economic informatics. This new direction combines economics, mathematics and computer science, and helps economists solve problems of optimizing the activities of enterprises, make strategically important decisions on industrial development and manage the production process.

The developed software base is based on mathematical models of economic processes and provides a flexible and reliable mechanism for predicting the economic effect of management decisions. With the help of computers, analytical problems that cannot be solved by humans can be quickly solved.

Recently, the computer has become an integral part of the workplace of a manager and economist.

Bibliography.

1. Figurnov. PC for beginners. M.: VSh – 1995.

2. Oseiko N. Accounting using a PC. Third edition. K.: SoftArt, 1996.

3. Information systems in economics. M.: VSh – 1996.

4. Richard B. Chase, Nicholas J. Aquilano. Production And Operations Management: A Life Cycle Approach. Fifth Edition. Boston, MA: Irwin – 1989.

5. Ventzel E.S. Operations research. M: VSh – 1983

6. Minu Mathematical programming M: Radio and communications 1978

Economic informatics

The phrase economic information (EI) came into use in the 60s with the introduction of computer technology into the sphere of economic management. Her research made it possible, firstly, to classify information (by place of origin (incoming, outgoing), by participation in the processing/storage process (initial, derivative, stored without processing, intermediate, result), in relation to management functions (planned, forecast , regulatory, design and technological, accounting, financial, etc.), etc.), and secondly, to identify a number of features that affect the organization of automated processing:

1. EI is specific in its presentation form. It is certainly reflected on tangible media in the form of primary and summary documents; to increase reliability, the transfer and processing is carried out only of legally formalized information, that is, if there is a signature on traditional or electronic documents (requires special means and organizational measures).
2. EI is volumetric. High-quality management of economic processes is impossible without detailed information about them. Improving management and increasing production volumes in the material and non-material spheres are accompanied by an increase in the accompanying information flows (requires increasing productivity of processing tools and communication channels).

Z.EI is cyclical. Most production and economic processes are characterized by repeatability of their constituent stages and information reflecting these processes (once created information processing programs can be reused and replicated).

4. EI reflects the results of production and economic activities using a system of natural and cost indicators. In this case, quantitative quantities and digital values are used (they are convenient to process).

Z.EI is specific in terms of processing methods. The processing process is dominated by arithmetic and, first of all, logical (for example, sorting or selection) operations, and the results are presented in the form of text documents, tables, charts and graphs (making it possible to limit oneself to a certain range of problem-oriented software tools).

No matter how complex and “intelligent” an automated data processing system is, its use is useless if the input data does not accurately reflect the properties of the problem domain. The role and importance of primary information cannot be overestimated. Therefore, it is important for any economist to know the technology of working with primary information.

To register any business transaction, that is, to obtain primary (initial) information about the processes occurring in the management object, it is necessary to perform such actions as identification, time reference, measurement.

Identification is an action, a process as a result of which the identifier of an object is established (recognized, determined). The object here can be the subject of labor (who performed the operation), and the object of labor (which part is processed), and the object of transfer (what is transferred), and the subject of transfer (from whom, to whom), etc.

An identifier is a combination of characteristics that is associated with an identification object and uniquely distinguishes it from any other object (in a given information system within a given class of objects). In other words, an identifier is a unique name for an object. The identifier can be both the digital code of the recipient and the security features of the banknote.

Depending on the specific circumstances, it is necessary to identify either only the type of object (for example, a model of a refrigerator, the denomination of a banknote, a type of fabric), or both the type and an instance of the object (an enterprise employee with his unique personnel number, smarkard).

Time binding (dating) is an action, a process, as a result of which the time/date (possibly the beginning and completion) of the operation is recorded (documented).

Measurement is the determination by some measure of the value of some quantity. Methods, means and units (pieces, kilograms, liters, rubles) of measurement significantly depend on the type and essence of the object of measurement. The unifying thing here is that it is during the measurement process that the primary data is formed.

The process of obtaining primary data has a number of features that must be kept in mind when creating automated system information processing.

First of all, it should be taken into account that data collection is a normal labor process, and it requires certain qualifications and the expenditure of effort and time. Moreover, the costs are not small, since data collection operations are often of a massive nature. In addition, primary data must accurately describe primary business transactions. In other words, the primary information must be reliable. But this is not enough. It must also be timely.

Structural components of EI. Economic indicators describe different entities, both simple and complex. Each entity (subject, process, phenomenon, object) has certain properties (weight, dimensions, price, etc.). A set of information reflecting any entity is called an information set or a composite unit of information. Typically, a collection of information has a hierarchical structure. For example, “Data about the supplier” includes his “F.I.0.”, “Address”, “Product nomenclature”, “Terms of delivery”. "Address" implies "Zip Code", "City", etc.

The level of detail of the information set is finite. The information set, indivisible further into semantic units, is called props. When describing information systems, its synonyms are used: word, data element, attribute.

Details (documents) - a set of formal elements as part of a transaction or document, the absence of which deprives the transaction or document of legal force; mandatory data provided current rules or laws for documents, without which documents cannot serve as a basis for modern operations. Although the details are the main element of economic information (date, amount, name, etc.), taken separately, they have no economic meaning. transformation information computer information society

There are two types of attributes: attribute attributes and basis attributes. If a prop describes a qualitative property of information (time or place of action, full name of the performer and name), then it is called a prop. If the attribute represents a quantitative characteristic (product volume in pieces, price in rubles, etc.), then it is called a basis attribute.

The combination of one basis attribute with one or more corresponding attribute attributes forms an indicator. An indicator is a qualitatively defined value that gives a quantitative characteristic of the displayed object (subject, process, phenomenon) and has economic meaning. This is an information set of the smallest composition, sufficient to form an independent message or form a document. For example, the information set “five pairs of women’s shoes” consists of the base attribute “five” and three attribute attributes: “pair”, “women’s” and “shoes”, has an economic meaning and is therefore an indicator. A set of logically related details that has legal force is called a document (Documented information (document) - information recorded on a tangible medium with details that allow it to be identified).

Problems of computer science

- research of information processes of any nature;
- development of information technology and creation of the latest information processing technology based on the results of research into information processes;
- solving scientific and engineering problems of creation, implementation and support effective use computer equipment and technology in all spheres of public life.

Computer science does not exist on its own, but is a complex scientific and technical discipline designed to create new information techniques and technologies to solve problems in other areas. It provides research methods and tools to other areas, even those where it is considered impossible to use quantitative methods due to the lack of formalizability of processes and phenomena. Particularly noteworthy in computer science are methods of mathematical modeling and methods of pattern recognition, the practical implementation of which became possible thanks to the achievements of computer technology.