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Novoyenisei branch of KGBPOU "Krasnoyarsk Polytechnic College" CLASSIFICATION OF FACTORS IN THE ANALYSIS OF ECONOMIC ACTIVITIES Completed by student gr. E-51 Soboleva T.V. Head: Bezborodova T.N. Classification of factors in analysis economic activity.
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All processes of economic activity of enterprises are interconnected, interdependent and conditional. Each phenomenon can be considered as a cause and as a result. The performance indicator depends on numerous and varied factors. All phenomena and processes of economic activity of enterprises are interconnected, interdependent and conditional. Some of them are directly related to each other, others - indirectly. Each phenomenon can be considered as a cause and as a result. The performance indicator depends on numerous and varied factors.
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Definition Factor analysis is a technique for a comprehensive and systematic study and measurement of the interaction of factors on the value of performance indicators. Factor analysis is a technique for a comprehensive and systematic study and measurement of the interaction of factors on the value of performance indicators.
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Types of factor analysis deterministic and stochastic direct and inverse single-stage and multi-stage static and dynamic retrospective and prospective Types of factor analysis: Deterministic and stochastic. Deterministic (functional) factor analysis is a technique for studying the influence of factors whose connection with the performance indicator is functional in nature. Stochastic (correlation) factor analysis is a technique for studying factors whose connection with an effective indicator is incomplete, probabilistic (correlation). 2) Direct and reverse. In direct factor analysis, the research is conducted in a deductive manner - from the general to the specific. Reverse factor analysis carries out the study of cause-and-effect relationships using the method of logical induction - from particular, individual factors to general ones. 3) Single-stage and multi-stage. The first type is used to study factors of only one level (one level) of subordination without detailing them into their component parts. In multi-stage factor analysis, factors are detailed into their component elements in order to study their behavior. 4) Static and dynamic. The first type is used when studying the influence of factors on performance indicators on the corresponding date. Another type is a technique for studying cause-and-effect relationships in dynamics. 5) Retrospective and prospective. Retrospective analysis is carried out for the most important reporting periods of business, mainly on the basis of official reporting and system accounting. Prospective (forecast) analysis examines the behavior of factors and performance indicators in the future.
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CLASSIFICATION OF FACTORS REPRESENTS THEIR DISTRIBUTION INTO GROUPS DEPENDING ON THE GENERAL CHARACTERISTICS. The classification of factors is their distribution into groups depending on common characteristics.
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Classification feature Groups of factors By their nature Natural - climatic Socio - economic Production - economic By the degree of impact on the results Basic Minor In relation to the object of study Internal External Depending on the team Objective Subjective By degree of prevalence General Specific By time of action Constant Variables By the nature of the action Extensive Intensive According to the properties of the reflected phenomena Quantitative Qualitative According to its composition Simple Complex According to the level of subordination (hierarchy) First order Second order, etc. If it is possible to measure influence Measurable Not measurable Classification of factors in the analysis of economic activity: By their nature: natural - climatic factors, taking into account the influence of which allows us to more accurately assess the results of the work of business entities; socio-economic factors contribute to a more complete use of the enterprise’s production resources and increase the efficiency of its work; production and economic factors determine the completeness and efficiency of use of the enterprise's production resources. According to the degree of impact on the results: secondary; basic. In relation to the object of study: internal, depending on the activities of the organization; external, independent of the organization’s activities. Depending on the team: objective, do not depend on the will and desire of employees; subjective, depending on the activities of legal and individuals. By degree of prevalence: general, which operate in all sectors of the economy; specific, which operate in a particular sector of the economy or enterprise. By time of action: constant, which influence the phenomenon being studied continuously throughout the entire time; variables that appear periodically, for example, the development of new technology, new types of products, new technology production. By the nature of the action: extensive, which are associated with a quantitative rather than a qualitative increase in the effective indicator; intensive, characterize the degree of effort and intensity of labor in the production process. According to the properties of the reflected phenomena: Quantitative, which express the quantitative certainty of the phenomena; Qualitative, they determine the internal qualities, characteristics, features of the objects being studied. In terms of their composition: simple, resulting from the action of one cause; complex, arising under the influence of a complex of reasons. By level of subordination (hierarchy): First order, which directly influence the performance indicator; Second order, etc., which determine the performance indicator indirectly, using first-level factors, are called second-level factors; Impact measurements where possible: Measurable; Not measurable. Individual factors on a performance indicator can be measured quantitatively. At the same time, there are a number of factors whose influence on the performance of enterprises cannot be directly measured.
Interrelation of economic phenomena. Introduction to factor analysis. Types of factor analysis, its main tasks.
All phenomena and processes of economic activity of enterprises are interconnected, interdependent and conditional. Some of them are directly related to each other, others indirectly. For example, the amount of gross output is directly influenced by factors such as the number of workers and the level of their labor productivity. All other factors influence this indicator indirectly.
Each phenomenon can be considered as a cause and as a consequence. For example, labor productivity can be considered, on the one hand, as the reason for changes in production volume and the level of its cost, and on the other hand, as a result of changes in the degree of mechanization and automation of production, improvement in labor organization, etc.
Each performance indicator depends on numerous and varied factors. The more detailed the influence of factors on the value of the performance indicator is studied, the more accurate the results of the analysis and assessment of the quality of work of enterprises. Hence, an important methodological issue in the analysis of economic activity is the study and measurement of the influence of factors on the value of the studied economic indicators. Without a deep and comprehensive study of factors, it is impossible to draw informed conclusions about the results of operations, identify production reserves, and justify plans and management decisions.
Under factor analysis understands the methodology for a comprehensive and systematic study and measurement of the impact of factors on the value of performance indicators.
The following are distinguished: types of factor analysis:
deterministic and stochastic;
direct and reverse;
single-stage and multi-stage;
static and dynamic;
retrospective and prospective (forecast).
Deterministic factor analysis is a methodology for studying the influence of factors whose connection with the performance indicator is functional in nature, i.e. when the effective indicator is presented in the form of a product, quotient or algebraic sum of factors.
Stochastic Analysis is a methodology for studying factors whose connection with a performance indicator, unlike a functional one, is incomplete and probabilistic (correlation). If with a functional (complete) dependence with a change in the argument there is always a corresponding change in the function, then with a correlation connection a change in the argument can give several values of the increase in the function depending on the combination of other factors that determine this indicator. For example, labor productivity at the same level of capital assets may not be the same at different enterprises. This depends on the optimal combination of other factors affecting this indicator.
At direct factor analysis The research is conducted in a deductive manner - from the general to the specific. Reverse factor analysis carries out the study of cause-and-effect relationships using the method of logical induction - from particular, individual factors to general ones.
Factor analysis can be single stage And multi-stage. The first type is used to study factors of only one level (one level) of subordination without detailing them into their component parts. For example, at = A X b. In multi-stage factor analysis, factors are detailed A And b into constituent elements in order to study their behavior. The detailing of factors can be continued further. In this case, the influence of factors at different levels of subordination is studied.
It is also necessary to distinguish static And dynamic factor analysis. The first type is used when studying the influence of factors on performance indicators on the corresponding date. Another type is a technique for studying cause-and-effect relationships in dynamics.
Finally, factor analysis can be retrospective, which studies the reasons for the increase in performance indicators over past periods, and promising, which examines the behavior of factors and performance indicators in perspective.
The main objectives of factor analysis are as follows.
1. Selection of factors that determine the performance indicators under study.
2. Classification and systematization of factors in order to provide an integrated and systematic approach to the study of their influence on the results of economic activity.
3. Determination of the form of dependence between factors and the performance indicator.
4. Modeling the relationships between performance and factor indicators.
5. Calculation of the influence of factors and assessment of the role of each of them in changing the value of the effective indicator.
6. Work with the factor model (its practical use for managing economic processes).
Selection of factors for analysis of one or another indicator is carried out on the basis of theoretical and practical knowledge acquired in this industry. In this case, they usually proceed from the principle: the larger the complex of factors studied, the more accurate the results of the analysis will be. At the same time, it is necessary to keep in mind that if this complex of factors is considered as a mechanical sum, without taking into account their interaction, without identifying the main, determining ones, then the conclusions may be erroneous. In ACD, an interconnected study of the influence of factors on the value of performance indicators is achieved through their systematization, which is one of the main methodological issues of this science.
An important methodological issue in factor analysis is determining the form of dependence between factors and performance indicators: functional or stochastic, direct or inverse, linear or curvilinear. It uses theoretical and practical experience, as well as methods for comparing parallel and dynamic series, analytical groupings of source information, graphical, etc.
Modeling of economic indicators (deterministic and stochastic) also represents a complex methodological problem in factor analysis, the solution of which requires special knowledge and practical skills in this industry. In this regard, this issue is given a lot of attention in this course.
The most important methodological aspect in ACD is influence calculation factors on the value of performance indicators, for which the analysis uses a whole arsenal of methods, the essence, purpose, scope of which and the calculation procedure are discussed in the following chapters.
And finally, the last stage of factor analysis - practical use of the factor model to calculate reserves for the growth of a productive indicator, to plan and predict its value when the production situation changes.
The meaning of factor classification. Main types of factors. The concept and difference between various types of factors in ACD.
The classification of factors is their distribution into groups depending on common characteristics. It allows you to gain a deeper understanding of the reasons for changes in the phenomena under study, and more accurately assess the place and role of each factor in the formation of the value of effective indicators.
The factors studied in the analysis can be classified according to different criteria (Fig. 5.1).
By their nature, factors are divided into natural-climatic, socio-economic and production-economic. Natural and climatic factors have a great influence on the performance results in agriculture, in the mining industry, forestry and other industries. Taking into account their influence allows us to more accurately assess the results of the work of business entities.
TO socio-economic factors include the living conditions of workers, the organization of cultural, sports and recreational work at the enterprise, the general level of culture and education of personnel, etc. They contribute to a more complete use of the enterprise’s production resources and increase the efficiency of its work.
Production and economic factors determine the completeness and efficiency of use of the enterprise’s production resources and the final results of its activities.
Based on the degree of impact on the results of economic activity, factors are divided into major and minor. TO main include factors that have a decisive impact on the performance indicator. Secondary those that do not have a decisive impact on the results of economic activity in the current conditions are considered. It should be noted here that the same factor, depending on the circumstances, can be both primary and secondary. The ability to identify the main, determining factors from a variety of factors ensures the correctness of the conclusions based on the results of the analysis.
Of great importance when studying economic phenomena and processes and assessing the results of enterprises’ activities is the classification of factors into internal And external, that is, on factors that depend and do not depend on the activities of a given enterprise. The main attention in the analysis should be paid to the study of internal factors that the enterprise can influence.
At the same time, in many cases, with developed production connections and relationships, the results of each enterprise are significantly influenced by the activities of other enterprises, for example, the uniformity and timeliness of supplies of raw materials, their quality, cost, market conditions, inflationary processes, etc. Often the results of enterprises are reflected in changes in the field of specialization and industrial cooperation. These factors are external. They do not characterize the efforts of a given team, but their study makes it possible to more accurately determine the degree of influence of internal causes and thereby more fully identify the internal reserves of production.
To correctly assess the activities of enterprises, factors must be divided into objective And subjective Objective ones, such as a natural disaster, do not depend on the will and desires of people. Unlike objective reasons, subjective reasons depend on the activities of legal entities and individuals.
According to the degree of prevalence, factors are divided into general And specific. General factors include factors that operate in all sectors of the economy. Specific are those that operate in a particular sector of the economy or enterprise. This division of factors allows us to more fully take into account the features individual enterprises, industries and make a more accurate assessment of their activities.
Factors are distinguished according to the period of influence on the results of economic activity: permanent And variables. Constant factors influence the phenomenon under study continuously, throughout the entire time. The impact of variable factors manifests itself periodically, for example, the development of new technology, new types of products, new production technology, etc.
Of great importance for assessing the activities of enterprises is the division of factors according to the nature of their action into intensive And extensive. Extensive factors include factors that are associated with a quantitative rather than a qualitative increase in the performance indicator, for example, an increase in the volume of production by expanding the sown area, increasing the number of livestock, the number of workers, etc. Intensive factors characterize the degree of effort and labor intensity in the production process, for example, increasing crop yields, animal productivity, and the level of labor productivity.
If the analysis aims to measure the influence of each factor on the results of economic activity, then they are divided into quantitative And high quality, complex And simple, straight And indirect, measurable And immeasurable.
Quantitative factors are considered that express the quantitative certainty of phenomena (number of workers, equipment, raw materials, etc.). Quality factors determine the internal qualities, characteristics and characteristics of the objects being studied (labor productivity, product quality, soil fertility, etc.).
Most of the factors studied are complex in composition and consist of several elements. However, there are also those that cannot be broken down into their component parts. In this regard, factors are divided into complex (complex) And simple (elemental). An example of a complex factor is labor productivity, and a simple one is the number of working days in the reporting period.
As already indicated, some factors have a direct impact on the performance indicator, while others have an indirect impact. Based on the level of subordination (hierarchy), factors of the first, second, third and subsequent levels of subordination are distinguished. TO first level factors These include those that directly affect the performance indicator. Factors that determine the performance indicator indirectly, using first-level factors, are called second level factors etc. In Fig. 5.2 shows that the factors of the first level are the average annual number of workers and the average annual production output per worker. The number of days worked by one worker and the average daily output are second-level factors relative to gross output. Factors of the third level include the length of the working day and average hourly output.
The impact of individual factors on the performance indicator can be quantified. At the same time, there are a number of factors whose influence on the performance of enterprises cannot be directly measured, for example, the provision of housing for personnel, childcare facilities, the level of personnel training, etc.
The need and significance of systematizing factors. Basic ways of systematizing factors in deterministic and stochastic analysis.
A systematic approach in ACD necessitates an interconnected study of factors, taking into account their internal and external relations, interaction and subordination, which is achieved through systematization. Systematization in general is the placement of the studied phenomena or objects in a certain order, identifying their relationship and subordination.
One way to systematize factors is to create deterministic factor systems. Create a factor system - means to present the phenomenon under study in the form of an algebraic sum, a quotient, or a product of several factors that determine its magnitude and are in functional dependence with it.
For example, the volume of gross output industrial enterprise can be represented as a product of two first-order factors: the average number of workers and the average annual output per worker per year, which in turn depends directly on the number of days worked by one worker on average per year and the average daily output per worker. The latter can also be decomposed into the length of the working day and average hourly output (Fig. 5.2).
The development of a deterministic factor system is achieved, as a rule, by detailing complex factors. Elementary ones (in our example - the number of workers, the number of days worked, the length of the working day) are not decomposed into factors, since they are homogeneous in their content. With the development of the system, complex factors are gradually detailed into less general ones, which in turn are even less general, gradually approaching elemental (simple) in their analytical content.
However, it should be noted that the development of factor systems to the required depth is associated with some methodological difficulties and, above all, with the difficulty of finding factors of a general nature that could be represented as a product, a particular one, or an algebraic sum of several factors. Therefore, deterministic systems usually cover the most general factors. Meanwhile, the study of more specific factors in ACD is significantly more important than general ones.
It follows that improving the methodology of factor analysis should be aimed at the interrelated study of specific factors, which are, as a rule, in a stochastic relationship with performance indicators.
Of great importance in the study of stochastic relationships is structural and logical analysis of the relationship between the studied indicators. It allows you to establish the presence or absence of cause-and-effect relationships between the studied indicators, study the direction of the connection, the form of dependence, etc., which is very important when determining the degree of their influence on the phenomenon under study and when generalizing the results of the analysis.
Analysis of the structure of the connection between the studied indicators in ACD is carried out using the construction structural and logical block diagram, which allows us to establish the presence and direction of the connection not only between the factors being studied and the performance indicator, but also between the factors themselves. By constructing a block diagram, you can see that among the factors being studied there are those that more or less directly affect the performance indicator, and those that affect not so much the performance indicator as each other.
For example, in Fig. Figure 5.3 shows the relationship between the cost per unit of crop production and factors such as crop yield, labor productivity, amount of fertilizer applied, quality of seeds, degree of mechanization of production.
First of all, it is necessary to establish the presence and direction of the relationship between the cost of production and each factor. Of course, there is a close connection between them. In this example, only crop yield has a direct impact on the cost of production. All other factors influence the cost of production not only directly, but also indirectly, through crop yields and labor productivity. For example, the amount of fertilizer applied to the soil helps to increase crop yields, which, other conditions being the same, leads to a reduction in the cost per unit of production. However, it is also necessary to take into account that an increase in the amount of fertilizer applied leads to an increase in the amount of costs per hectare of crops. And if the amount of costs increases at a higher rate than the yield, then the cost of production will not decrease, but increase. This means that the relationship between these two indicators can be both direct and inverse. It similarly affects the cost of production and the quality of seeds. Purchasing elite, high-quality seeds causes an increase in costs. If they increase to a greater extent than the yield from using higher quality seeds, then the cost of production will increase, and vice versa.
The degree of mechanization of production affects the cost of production both directly and indirectly. An increase in the level of mechanization causes an increase in the cost of maintaining fixed assets of production. However, at the same time, labor productivity increases and productivity increases, which helps reduce production costs.
The study of relationships between factors shows that of all the factors studied, there is no cause-and-effect relationship between the quality of seeds, the amount of fertilizers and the mechanization of production. There is also no direct inverse relationship between these indicators and the level of crop yield. All other factors directly or indirectly influence each other.
Thus, the systematization of factors allows us to more deeply study the relationship of factors in the formation of the value of the studied indicator, which has a very important at the next stages of analysis, especially at the stage of modeling the indicators under study.
The essence and significance of modeling, requirements for it. Basic types of factorial deterministic models. Methods for transforming factor models. Modeling rules.
One of the tasks of factor analysis is to model the relationships between performance indicators and the factors that determine their value.
Modeling - This is one of the most important methods of scientific knowledge, with the help of which a model (conventional image) of the object of study is created. Its essence lies in the fact that the relationship between the indicator being studied and the factor indicators is conveyed in the form of a specific mathematical equation.
In factor analysis there are deterministic models (functional) and stochastic (correlation). Using deterministic factor models, the functional relationship between the performance indicator (function) and factors (arguments) is studied.
When modeling deterministic factor systems, a number of requirements must be met.
1. The factors included in the model, and the models themselves, must have a clearly expressed character, really exist, and not be invented abstract quantities or phenomena.
2. The factors that are included in the system must not only be necessary elements of the formula, but also be in a cause-and-effect relationship with the indicators being studied. In other words, the constructed factor system must have cognitive value. Factor models that reflect cause-and-effect relationships between indicators have significantly greater cognitive value than models created using mathematical abstraction techniques. The latter can be illustrated as follows. Let's take two models:
1)VP=CR X GW:
2) GV=VP/CR, Where VP - gross output of the enterprise; CR - number of employees at the enterprise; GV - average annual production per worker.
In the first system, the factors are in a causal relationship with the effective indicator, and in the second - in a mathematical relationship. This means that the second model, built on mathematical dependencies, has less cognitive significance than the first.
3. All indicators of the factor model must be quantitatively measurable, i.e. must have a unit of measurement and the necessary information security.
4. The factor model must provide the ability to measure the influence of individual factors, which means that it must take into account the proportionality of changes in the effective and factor indicators, and the sum of the influence of individual factors must be equal to the total increase in the effective indicator.
In deterministic analysis, the following types of the most common factor models are distinguished.
1. Additive models:
They are used in cases where the effective indicator is an algebraic sum of several factor indicators.
2. Multiplicative models:
This type of model is used when the performance indicator is a product of several factors.
3. Multiple models:
They are used when the effective indicator is obtained by dividing one factor indicator by the value of another.
4. Mixed (combined) models - this is a combination in various combinations of previous models:
Modeling of multiplicative factor systems in ACD it is carried out by sequentially dividing the factors of the original system into factor factors. For example, when studying the process of formation of production volume (see Fig. 5.2), you can use such deterministic models as:
These models reflect the process of detailing the original factor system of a multiplicative form and expanding it by dividing complex factors into factors. The degree of detail and expansion of the model depends on the purpose of the study, as well as on the possibilities of detailing and formalizing indicators within the established rules.
Similarly carried out modeling of additive factor systems due to the division of one or several factor indicators into component elements.
As is known, the volume of product sales is equal to:
VRP =VBP -VAND,
Where VBP - production volume; VAND - volume of on-farm use of products.
On the farm, the products were used as seeds (C) and feed (TO). Then the given original model can be written as follows: VRP =VBP - (C + K).
To class multiple models The following methods of their transformation are used: lengthening, formal decomposition, expansion and contraction.
First method involves lengthening the numerator of the original model by replacing one or more factors with the sum of homogeneous indicators. For example, the cost per unit of production can be represented as a function of two factors: changes in the amount of costs (3) and the volume of output (VBP). The initial model of this factor system will have the form
If the total amount of costs (3) is replaced by their individual elements, such as wages(3P), raw materials and supplies (SM), depreciation of fixed assets (A), overhead costs (HP) etc., then the deterministic factor model will have the form of an additive model with a new set of factors:
Where X 1 - labor intensity of products; X 2 - material intensity of products; X 3 - capital intensity of products; X 4 - overhead level.
Formal decomposition method factor system involves lengthening the denominator of the original factor model by replacing one or more factors with the sum or product of homogeneous indicators. If IN = L+M+N+P, then
As a result, we obtained a final model of the same type as the original factor system (multiple model). In practice, such decomposition occurs quite often. For example, when analyzing the production profitability indicator (R):
where P is the amount of profit from sales of products; 3 - the amount of costs for production and sales of products. If the sum of costs is replaced by its individual elements, the final model as a result of the transformation will take on the following form:
The cost of one ton-kilometer depends on the amount of costs for maintaining and operating the vehicle (3) and on its average annual output (GW). The initial model of this system will look like: C tkm = 3 / GV. Considering that the average annual output of a car, in turn, depends on the number of days worked by one car per year (D), shift duration (P) and average hourly output (ChV), we can significantly lengthen this model and decompose the increase in cost into more factors:
The expansion method involves expanding the original factor model by multiplying the numerator and denominator of the fraction by one or more new indicators. For example, if the original model
introduce a new indicator, the model will take the form
The result was a final multiplicative model in the form of a product of a new set of factors.
This modeling method is very widely used in analysis. For example, the average annual output per worker (labor productivity indicator) can be written as follows: GV = VP / CR. If you enter an indicator such as the number of days worked by all employees (D), then we get the following model of annual output:
Where DV - average daily output; D - number of days worked by one employee.
After introducing the indicator of the number of hours worked by all employees (G), we obtain a model with a new set of factors: average hourly output (ChV), number of days worked by one employee (D) and duration of the working day (I):
The reduction method involves creating a new factor model by dividing the numerator and denominator of the fraction by the same indicator:
In this case, the final model is the same type as the original one, but with a different set of factors.
And again practical example. As is known, the economic profitability of an enterprise is calculated by dividing the amount of profit ( P) on the average annual cost of the main and working capital enterprises (KL):
R=P/KL.
If we divide the numerator and denominator by the volume of product sales (turnover), we obtain a multiple model, but with a new set of factors: return on sales and capital intensity of products:
And one more example. Capital productivity (CR) is determined by the ratio of gross ( VP) or commercial products (TP) to the average annual cost of fixed production assets (OPF):
Dividing the numerator and denominator by the average annual number of workers (CR), we get a more meaningful multiple model with other factor indicators: average annual production per worker (GV), characterizing the level of labor productivity and capital-labor ratio (Fv):
It should be noted that in practice, several methods can be used sequentially to transform the same model. For example:
Where FO - capital productivity; RP - volume of products sold (revenue); C - cost of goods sold; P- profit; OPF-average annual cost of fixed production assets; OS - average working capital balances.
In this case, to transform the original factor model, which is built on mathematical dependencies, methods of lengthening and expansion were used. The result is a more meaningful model, which has greater educational value, since it takes into account the cause-and-effect relationships between indicators. The resulting final model allows us to study how the profitability of fixed assets of production, the relationship between fixed and working capital, as well as the working capital turnover ratio.
Thus, performance indicators can be decomposed into their component elements (factors) in various ways and are presented in the form of various types of deterministic models. The choice of modeling method depends on the object of study, the goal, as well as the professional knowledge and skills of the researcher.
The process of modeling factor systems is a very complex and crucial moment in ACAD. The final results of the analysis depend on how realistically and accurately the created models reflect the relationship between the studied indicators.
The factors studied in the analysis can be classified according to different criteria (Table 2.1), which makes it possible to more accurately assess the place and role of each factor in shaping the value of performance indicators.
By nature factors are divided into natural-climatic, socio-economic and production-economic.
Natural and climatic factors have a major impact on performance in agriculture, mining, forestry and other industries. Taking into account their influence allows us to more accurately assess the results of the work of business entities.
TO socio-economic factors include the living conditions of workers, the organization of cultural, sports and recreational work at the enterprise, the general level of culture and education of personnel, etc. They contribute to a more complete use of the enterprise’s production resources and increase the efficiency of its work.
Production and economic factors determine the completeness and efficiency of use of the enterprise’s production resources and the final results of its activities.
By degree of impact on results economic activity factors are divided into primary and secondary. Basic factors, unlike secondary, have the most significant impact on the performance indicator. It should be noted that the same factor, depending on the circumstances, can be both primary and secondary. The ability to identify the main, determining factors from a variety of factors ensures the correctness of conclusions based on the results of the analysis.
In relation to the object of study factors are classified into internal And external, those. dependent and independent of the activities of this enterprise. The main focus of the analysis should be
but pay attention to the study of internal factors that the enterprise can influence.
At the same time, in many cases, in the presence of developed production connections and relationships, the results of each enterprise are significantly influenced by the activities of other enterprises, for example, the uniformity and timeliness of supplies of raw materials, materials, their quality, cost, market conditions, inflationary processes, etc. factors are external. They do not characterize the efforts of a given team, but their study makes it possible to more accurately determine the degree of influence of internal causes and thereby more fully identify the internal reserves of production.
According to the degree of dependence on the business entity factors are divided into objective(not dependent on the will and desires of people, for example a natural disaster) and subjective(depending on the activities of legal entities and individuals).
By prevalence factors are divided into general(operating in all sectors of the economy) and specific(operating in a particular sector of the economy or enterprise). This division allows us to more fully take into account the characteristics of individual enterprises and industries and more accurately assess their activities.
By duration of impact on performance results distinguish factors permanent(having an influence on the phenomenon being studied continuously throughout the entire time) and variables(the impact of which is periodic, for example, the development of new technology, new types of products, new production technology, etc.)
By the nature of the action factors are divided into intense, which characterize the degree of effort, labor intensity in the production process (for example, increasing crop yields, increasing livestock productivity, labor productivity levels), and extensive, which are associated with a quantitative rather than a qualitative increase in the performance indicator (for example, an increase in the volume of production by expanding the sown area, increasing the number of animals, the number of workers, etc.)
If the analysis aims to measure the influence of each factor on the results of economic activity, then they are divided into quantitative and qualitative, complex and simple, direct and indirect, measurable and immeasurable.
Quantitative factors express the quantitative certainty of phenomena (number of workers, equipment, raw materials, etc.).
Quality factors determine the internal qualities, characteristics and characteristics of the objects being studied (labor productivity, product quality, soil fertility, etc.).
Depending on the composition factors are divided into complex(complex), consisting of several elements, and simple(elemental), which are not decomposed into component parts. An example of a complex factor is labor productivity, a simple one is the number of working days in the reporting period.
As already indicated, some factors have a direct and others have an indirect impact on the performance indicator.
By level of subordination (hierarchy) factors of the first, second, third and so on levels of subordination are distinguished. Factors of the first level directly affect the performance indicator. Factors of the second level determine the performance indicator indirectly, with the help of factors of the first level, etc. (Fig. 2.2).
Where possible, impact measurements for the effective indicator, the factors are divided into parametric(measurable) and nonparametric(non-measurable - for example, the provision of housing for workers, the level of personnel training, etc.).
The meaning of factor classification. Main types of factors. The concept and difference between various types of factors in ACD.
The classification of factors is their distribution into groups depending on common characteristics. It allows you to gain a deeper understanding of the reasons for changes in the phenomena under study, and more accurately assess the place and role of each factor in the formation of the value of effective indicators.
The factors studied in the analysis can be classified according to different criteria (Fig. 5.1).
By their nature, factors are divided into natural-climatic, socio-economic and production-economic. Natural and climatic factors have a great impact on the results of activities in agriculture, mining, forestry and other industries. Taking into account their influence allows us to more accurately assess the results of the work of business entities.
TO socio-economic factors include the living conditions of workers, the organization of cultural, sports and recreational work at the enterprise, the general level of culture and education of personnel, etc. They contribute to a more complete use of the enterprise’s production resources and increase the efficiency of its work.
Production and economic factors determine the completeness and efficiency of use of the enterprise’s production resources and the final results of its activities.
Based on the degree of impact on the results of economic activity, factors are divided into major and minor. TO main include factors that have a decisive impact on the performance indicator. Secondary those that do not have a decisive impact on the results of economic activity in the current conditions are considered. It should be noted here that the same factor, depending on the circumstances, can be both primary and secondary. The ability to identify the main, determining factors from a variety of factors ensures the correctness of the conclusions based on the results of the analysis.
Of great importance when studying economic phenomena and processes and assessing the results of enterprises’ activities is the classification of factors into internal And external, that is, on factors that depend and do not depend on the activities of a given enterprise. The main attention in the analysis should be paid to the study of internal factors that the enterprise can influence.
At the same time, in many cases, with developed production connections and relationships, the results of each enterprise are significantly influenced by the activities of other enterprises, for example, the uniformity and timeliness of supplies of raw materials, their quality, cost, market conditions, inflationary processes, etc. Often the results of enterprises' work are reflected in changes in the field of specialization and production cooperation. These factors are external. They do not characterize the efforts of a given team, but their study makes it possible to more accurately determine the degree of influence of internal causes and thereby more fully identify the internal reserves of production.
To correctly assess the activities of enterprises, factors must be divided into objective And subjective Objective ones, such as a natural disaster, do not depend on the will and desires of people. Unlike objective reasons, subjective reasons depend on the activities of legal entities and individuals.
According to the degree of prevalence, factors are divided into general And specific. General factors include factors that operate in all sectors of the economy. Specific are those that operate in a particular sector of the economy or enterprise. This division of factors allows us to more fully take into account the characteristics of individual enterprises and industries and make a more accurate assessment of their activities.
Factors are distinguished according to the period of influence on the results of economic activity: permanent And variables. Constant factors influence the phenomenon under study continuously, throughout the entire time. The impact of variable factors manifests itself periodically, for example, the development of new technology, new types of products, new production technology, etc.
Of great importance for assessing the activities of enterprises is the division of factors according to the nature of their action into intensive And extensive. Extensive factors include factors that are associated with a quantitative rather than a qualitative increase in the performance indicator, for example, an increase in the volume of production by expanding the sown area, increasing the number of livestock, the number of workers, etc. Intensive factors characterize the degree of effort and labor intensity in the production process, for example, increasing crop yields, animal productivity, and the level of labor productivity.
If the analysis aims to measure the influence of each factor on the results of economic activity, then they are divided into quantitative And high quality, complex And simple, straight And indirect, measurable And immeasurable.
Quantitative factors are considered that express the quantitative certainty of phenomena (number of workers, equipment, raw materials, etc.). Quality factors determine the internal qualities, characteristics and characteristics of the objects being studied (labor productivity, product quality, soil fertility, etc.).
Most of the factors studied are complex in composition and consist of several elements. However, there are also those that cannot be broken down into their component parts. In this regard, factors are divided into complex (complex) And simple (elemental). An example of a complex factor is labor productivity, and a simple one is the number of working days in the reporting period.
As already indicated, some factors have a direct impact on the performance indicator, while others have an indirect impact. Based on the level of subordination (hierarchy), factors of the first, second, third and subsequent levels of subordination are distinguished. TO first level factors These include those that directly affect the performance indicator. Factors that determine the performance indicator indirectly, using first-level factors, are called second level factors etc. In Fig. 5.2 shows that the factors of the first level are the average annual number of workers and the average annual production output per worker. The number of days worked by one worker and the average daily output are second-level factors relative to gross output. Factors of the third level include the length of the working day and average hourly output.
The impact of individual factors on the performance indicator can be quantified. At the same time, there are a number of factors whose influence on the performance of enterprises cannot be directly measured, for example, the provision of housing for personnel, childcare facilities, the level of personnel training, etc.
See also:
Factor in economic analysis are called active forces that cause positive or negative changes in the state of an object and in the indicators that reflect it. The concept of “factor” is used in economic analysis in 2 meanings:
Classification of factors in economic analysis:
By their nature, factors are divided into natural, socio-economic and production-economic.
Natural factors have a great influence on the results of activities in agriculture, forestry and other industries. Taking into account their influence makes it possible to more accurately assess the results of the work of business entities. Socio-economic factors include the living conditions of workers, the organization of health-improving work in enterprises with hazardous production, the general level of personnel training, etc. They contribute to a more complete use of the enterprise’s production resources and increase the efficiency of its work.
Production and economic factors determine the completeness and efficiency of use of the enterprise's production resources and the final results of its activities. Factors are divided into internal and external, depending on whether they are affected by the activities of a given enterprise or not. The analysis focuses on internal factors, which the enterprise can influence.
In the process of an organization's work, some factors influence the indicator under study continuously throughout the entire time. Such factors are called constants. Factors whose influence appears periodically are called variables (for example, the introduction of new technology, new types of products). Of great importance for assessing the activities of enterprises is the division of factors according to the nature of their action into intensive and extensive. Extensive factors include factors that are associated with changes in quantitative, rather than qualitative, characteristics of the functioning of an enterprise. An example is an increase in the volume of production due to an increase in the number of workers. Intensive factors characterize the qualitative side of the production process. An example would be an increase in production volume by increasing the level of labor productivity. Most of the factors studied are complex in composition and consist of several elements.
