Called factor analysis. The main types of factor analysis are deterministic analysis and stochastic analysis.

Deterministic factor analysis is based on a methodology for studying the influence of such factors, the relationship of which with a general economic indicator is functional. The latter means that the generalizing indicator is either a product, a quotient of division, or an algebraic sum of individual factors.

Stochastic factor analysis is based on a methodology for studying the influence of such factors, the relationship of which with a general economic indicator is probabilistic, otherwise - correlation.

In the presence of a functional relationship with a change in the argument, there is always a corresponding change in the function. If there is a probabilistic relationship, a change in the argument can be combined with several values ​​of the change in the function.

Factor analysis is also divided into straight, otherwise deductive analysis and back(inductive) analysis.

First type of analysis carries out the study of the influence of factors by a deductive method, that is, in the direction from the general to the specific. In reverse factor analysis the influence of factors is studied inductively - in the direction from particular factors to general economic indicators.

Classification of factors influencing the efficiency of an organization

Factors, the influence of which is studied during the study, are classified according to various signs. First of all, they can be divided into two main types: internal factors, depending on the activity of this, and external factors , independent of this organization.

Internal factors, depending on the magnitude of their impact on, can be divided into major and minor. The main ones include factors related to the use of materials and materials, as well as factors determined by supply and sales activities and some other aspects of the functioning of the organization. The main factors have a fundamental impact on general economic indicators. External factors beyond the control of a given organization are determined by natural-climatic (geographical), socio-economic, and foreign economic conditions.

Depending on the duration of their impact on economic indicators, we can distinguish constant and variable factors. The first type of factors has an impact on economic indicators that is not limited in time. Variable factors affect economic indicators only over a certain period of time.

Factors can be divided into extensive (quantitative) and intensive (qualitative) based on the essence of their influence on economic indicators. So, for example, if the influence of labor factors on the volume of output is studied, then a change in the number of workers will be an extensive factor, and a change in the labor productivity of one worker will be an intensive factor.

Factors influencing economic indicators, according to the degree of their dependence on the will and consciousness of the organization’s employees and other persons, can be divided into objective and subjective factors. Objective factors may include weather conditions and natural disasters that do not depend on human activity. Subjective factors depend entirely on people. The vast majority of factors should be classified as subjective.

Factors can also be divided depending on the scope of their action into factors of unlimited and factors of limited action. The first type of factors operates everywhere, in all sectors of the national economy. The second type of factors influences only within an industry or even a separate organization.

According to their structure, factors are divided into simple and complex. The overwhelming majority of factors are complex, including several components. At the same time, there are also factors that cannot be separated. For example, capital productivity can serve as an example of a complex factor. The number of days the equipment was used during a given period is a simple factor.

According to the nature of the influence on general economic indicators, they are distinguished direct and indirect factors. Thus, a change in products sold, although it has an inverse effect on the amount of profit, should be considered direct factors, that is, a first-order factor. A change in the amount of material costs has an indirect effect on profit, i.e. affects profit not directly, but through cost, which is a first-order factor. Based on this, the level of material costs should be considered a second-order factor, that is, an indirect factor.

Depending on whether it is possible to quantify the influence of a given factor on a general economic indicator, a distinction is made between measurable and unmeasurable factors.

This classification is closely interconnected with the classification of reserves for increasing the efficiency of economic activities of organizations, or, in other words, reserves for improving the analyzed economic indicators.

Factor economic analysis

Those signs that characterize the cause are called factorial, independent. The same signs that characterize the investigation are usually called resultant, dependent.

The set of factor and resultant characteristics that are in the same cause-and-effect relationship is called factor system. There is also the concept of a factor system model. It characterizes the relationship between the resultant characteristic, denoted as y, and the factor characteristics, denoted as . In other words, the factor system model expresses the relationship between general economic indicators and individual factors influencing this indicator. In this case, other economic indicators act as factors, representing the reasons for changes in the general indicator.

Factor system model can be expressed mathematically using the following formula:

Establishing dependencies between generalizing (resulting) and influencing factors is called economic-mathematical modeling.

We study two types of relationships between generalizing indicators and the factors influencing them:

• functional (otherwise - functionally determined, or strictly determined connection.)
• stochastic (probabilistic) connection.

Functional connection- this is a relationship in which each value of a factor (factorial characteristic) corresponds to a completely definite non-random value of a generalizing indicator (resultative characteristic).

Stochastic communication- this is a relationship in which each value of a factor (factor characteristic) corresponds to a set of values ​​of a general indicator (resultative characteristic). Under these conditions, for each value of factor x, the values ​​of the general indicator y form a conditional statistical distribution. As a result, a change in the value of factor x only on average causes a change in the general indicator y.

In accordance with the two types of relationships considered, a distinction is made between methods of deterministic factor analysis and methods of stochastic factor analysis. Consider the following diagram:

Methods used in factor analysis. Scheme No. 2

The greatest completeness and depth of analytical research, the greatest accuracy of analysis results is ensured by the use of economic and mathematical research methods.

These methods have a number of advantages over traditional and statistical methods of analysis.

Thus, they provide a more accurate and detailed calculation of the influence of individual factors on changes in the values ​​of economic indicators and also make it possible to solve a number of analytical problems that cannot be done without the use of economic and mathematical methods.

Factor analysis is understood as a method of complex and systematic study and measurement of factors for the value of effective indicators.

The following types of factor analysis are distinguished: deterministic (functional)

stochastic (probabilistic)

Deterministic factor analysis is a technique for assessing the influence of factors whose connection with the performance indicator is functional in nature, i.e. the effective indicator can be presented as a product, quotient or algebraic sum of factors.

Methods of deterministic factor analysis:

chain substitution method

index

integral

absolute differences

relative differences, etc.

Stochastic Analysis – a methodology for studying factors whose connection with an effective indicator, unlike a functional one, is incomplete, probabilistic.

Methods of stochastic factor analysis:

correlation analysis

regression analysis

dispersive

component

modern multivariate factor analysis

discriminant

Basic methods of deterministic factor analysis

THE CHAIN ​​SUBSTITUTION METHOD is the most universal; it is used to calculate the influence of factors in all types of factor models: addition, multiplication, division and mixed.

This method allows you to determine the influence of individual factors on changes in the value of the performance indicator by replacing the base value of each factor indicator with the actual value in the reporting period. For this purpose, a number of conditional values ​​of the performance indicator are determined, which take into account the change in one, then two, three, etc. factors, assuming that the rest do not change.

Comparing the value of an effective indicator before and after changing the level of one or another factor allows us to exclude the influence of all factors except one and determine its impact on the increase in the effective indicator.

The algebraic sum of the influence of factors must necessarily be equal to the total increase in the effective indicator. The absence of such equality indicates mistakes have been made.

INDEX METHOD is based on relative indicators of dynamics, spatial comparisons, plan implementation (indices), which are defined as the ratio of the level of the analyzed indicator in the reporting period to its level in the base period (or to the planned or other object).

Using indices, you can identify the influence of various factors on changes in performance indicators in multiplication and division models.

The INTEGRAL METHOD is a further logical development of the considered methods, which have a significant drawback: when using them, they assume that the factors change independently of each other. In fact, they change together, are interconnected, and from this interaction an additional increase in the effective indicator is obtained, which is added to one of the factors, usually the last one. In this regard, the magnitude of the influence of factors on the change in the performance indicator changes depending on the place in which one or another factor is placed in the model under study.

When using the INTEGRAL method, the error in calculating the influence of factors is distributed equally between them, and the order of substitution does not matter. The error distribution is carried out using special models.

Types of finite factor systems, the most frequently encountered in the analysis of economic activity:

additive models

multiplicative models

;

multiple models

;
;
;,

Where y– effective indicator (initial factor system);

x i– factors (factor indicators).

In relation to the class of deterministic factor systems, the following are distinguished: basic modeling techniques.

,

those. multiplicative model of the form
.

3. Factor system reduction method. Initial factor system
. If we divide both the numerator and denominator of the fraction by the same number, we get a new factor system (in this case, of course, the rules for selecting factors must be followed):

.

In this case we have a finite factor system of the form
.

Thus, the complex process of forming the level of the studied indicator of economic activity can be decomposed using various techniques into its components (factors) and is presented in the form of a model of a deterministic factor system.

Modeling the return on capital indicator of an enterprise ensures the creation of a five-factor profitability model, which includes all indicators of intensification of the use of production resources.

We will conduct a profitability analysis using the data in the table.

CALCULATION OF KEY INDICATORS FOR THE ENTERPRISE FOR TWO YEARS

Indicators	Legend	First (base) year (0)	Second (reporting) year (1)	Deviation, %
1. Products (sales at selling prices without indirect taxes), thousand rubles.
2. a) Production personnel, people
b) Remuneration with accruals, thousand rubles.
3. Material costs, thousand rubles.
4. Depreciation, thousand rubles.
5. Fixed production assets, thousand rubles.
6. Working capital in inventory, thousand rubles.	E 3
7. a) Labor productivity (page 1:page 2a), rub.	λ R
b) Products worth 1 rub. wages (line 1: line 2b), rub.	λ U
8. Material productivity (page 1: page 3), rub.	λ M
9. Depreciation return (page 1: page 4), rub.	λ A
10. Capital productivity (page 1: page 5), rub.	λ F
11. Turnover working capital(page 1:page 6), speed	λ E
12. Cost of sales (line 2b+line 3+line 4), thousand rubles.	S P
13. Profit from sales (page 1 + page 12), thousand rubles.	P P

Based on the basic indicators, we will calculate the indicators of intensification of production resources (rub.)

Indicators	Legend	First (base) year (0)	Second (reporting) year (1)
1. Payment intensity (labor intensity) of products
2. Material consumption of products
3 Depreciation capacity of products
4. Capital intensity of production
5. Working capital consolidation ratio

Five-factor model of return on assets (advanced capital)

.

We will illustrate the methodology for analyzing the five-factor model of return on assets using the method of chain substitutions.

First, let's find the profitability value for the base and reporting years.

For base year:

For the reporting year:

The difference in the profitability ratios of the reporting and base years was 0.005821, and as a percentage - 0.58%.

Let's look at how the five factors mentioned above contributed to this increase in profitability.

In conclusion, we will compile a summary of the influence of factors on the deviation of profitability of the 2nd year compared to the 1st (base) year.

Total deviation, % 0.58

Including due to the influence of:

labor intensity +0.31

material consumption +0.28

depreciation capacity 0

Total cost: +0.59

capital intensity −0.07

working capital turnover +0.06

Total advance payment −0.01

Any commercial enterprise operating in the market in a fairly tough competitive environment is obliged to effectively manage available internal resources and respond in a timely manner to changing external conditions. These goals are pursued by the corresponding analytical activities that will be discussed in the publication.

Factor analysis of profit

The object of close attention of the analyst is the profit of the enterprise, since it reflects the efficiency of the company, its liquidity and solvency. Profit acts as an indicator, reacting to any changes external environment and within the company, so it is important to be able to analyze this indicator, correctly assessing the degree of impact of all criteria.

Factor analysis of a company's net profit considers two influencing blocks: external and internal.

Factors that an enterprise is able to influence are considered internal. For example, a firm can influence profits because capacity utilization and the level of technology used affect the quality of its products. It is more difficult with non-production factors, such as the reaction of personnel to changes in working conditions, logistics, etc.

External factors are understood as factors of market realities that the company cannot control, but takes into account. For example, it is impossible to influence market conditions, inflation levels, distance from resources, climate conditions, changes in state tariffs, violation of agreements by partners, etc.

Factor analysis of net profit is a component of the analysis of a company’s financial activities. It is used to determine the degree of influence of various indicators on the result. For example, they study:

• dynamics of changes in revenue;
• increase in sales volume;
• impact on profit of sales dynamics, price and cost changes.

Analyze the indicators by comparing the results of two specific periods. The analysis begins with a grouping of factors affecting profit. Net profit is defined as revenue reduced by cost, taxes, selling, administrative and other expenses.

Factor analysis is based on the study of changes in each factor influencing the amount of profit, i.e., the analysis of changes in net profit in the period under review is carried out by comparing changes in all its component values.

Factor analysis of net profit: calculation example

Let us consider in more detail all stages of the analysis of the listed factors based on the data in the table:

Meaning	Sales volume (t.r.) per		Absolute deviation
	last year	reporting year	(gr 3 - gr2)	100 x ((gr 3 / gr2)) – 100
Cost price

Let's conduct a factor analysis of net profit. Our example is simplified and based on the calculation (using the formulas in the table):

• absolute values ​​of deviations in revenue and cost data for the reporting period in comparison with the previous year;
• increase in indicators in %.

Conclusion: during the reporting year, the company’s net profit increased by 1,000 thousand rubles compared to last year. A negative factor was the increase in production costs, amounting to 11.2% compared to the previous year. It is necessary to pay attention to the increase in cost and identify the causes of the phenomenon, since its increase significantly outpaces the growth of profits.

Having simplified the task and analyzed the indicators, we found out that it is necessary to conduct a more detailed study of the cost, since in our example it consists of several indicators and the calculation should be carried out by groups of all costs: production, commercial and administrative. Having expanded the block of initial data, we will proceed to factor analysis of sales profit and determine the main changing criteria.

Factor analysis of sales profit: calculation example

Meaning	Sales volume (t.r.) per		Absolute deviation
	last year	reporting year	(gr 3 – gr 2)	100 x ((gr 3 / gr 2)) – 100
Cost price
Business expenses
Management expenses
Revenue from sales
Price change index
Sales volume at comparable prices

Let's define the influence:

1. Sales volume multiplied by profit by volume change:
   • 73,451 tr. (83,000 / 1.13)
   • the actual sales volume, taking into account changes, amounted to 88.5% (73,451 / 83,000 x 100), i.e., sales volume was reduced by 11.5% (100 - 88.5).
   • because of this, sales profit actually decreased by 1,495 thousand rubles. (13,000 x (-0.115) = -1495).
2. Product range:
   • actual sales calculated at the base cost of 47,790 thousand rubles. (54,000 x 0.885);
   • profit for the reporting year, calculated at base costs and prices (AUR and selling expenses) RUB 16,661 thousand. (73,451 – 47,790 – 4000 – 5000). Those. the change in the composition of the assortment entailed a change in profit by 5156 thousand rubles. (16,661 – (13,000 x 0.885). This means that the specific gravity products with higher profitability.
3. Costs in terms of basis:
   • (54,000 x 0.885) – 60,000 = – 12,210 thousand rubles. – the cost has increased, which means that the profit from sales has decreased by the same amount.
4. AUR and commercial expenses, comparing their absolute values:
   • commercial expenses increased by 6,000 thousand rubles. (10,000 – 4000), i.e., profit has decreased;
   • by reducing the AUR by 1000 thousand rubles. (4000 – 5000) profit increased.
5. Sales prices, comparing sales volumes at base and reporting prices:
   • 83,000 – 73,451 = 9,459 thousand rubles.
   • Let's calculate the influence of all factors:
   • 1495 + 5156 – 12 210 – 6000 + 1000 + 9459 = – 4090 thousand rubles.

Conclusion: A significant increase in cost occurred against the backdrop of rising prices for raw materials and tariffs. The decrease in sales volume had a negative impact, although the company updated its range by releasing a number of products with higher profitability. In addition, business expenses have increased significantly. The company's profit growth reserves include increasing sales volumes, producing profitable products, and reducing production costs and business expenses.

Coursework in the discipline

"Industrial and Regional Aspects in Entrepreneurship"

On the topic “Methodology of factor analysis”

Completed by: Syrcina U.O.

5th year, SEF, Full-time

Checked by: Charyev R. M.

Associate Professor, Department of Economics

and management

Moscow 2008

Introduction

In today's economic conditions, an enterprise is forced to independently determine the prospects for its development. The successful solution of pressing economic problems, of course, depends on the development of the theory of activity analysis, which makes it possible to determine the effectiveness of the economic activity of an enterprise and to identify patterns of changes in the main results of its activities.

One of the most important tasks financial analysis any economic phenomenon – “... identification of factors, the level and changes of which have a decisive influence on the formation and change in the level of the phenomenon, considered as effective in relation to these factors.”

The value of the general indicator of the activity of structural divisions and the entire production formation depends on large number factors acting either in a certain sequence or simultaneously, in different directions and with varying strength. This dependence may have different character: probabilistic, in which the influence of one quantity on a change in another may have a possible (probabilistic) character;
or deterministic, meaning the dependence of the effective indicator on factors: each factor value corresponds to one single value of the effective indicator. Each performance indicator depends on numerous factors. The more detailed the influence of factors on the value of the indicator is considered, the more accurate the results of the analysis and assessment of the quality of the decision made. In some situations, without a deep and comprehensive study of the direct influence of factors, it is impossible to draw reasonable conclusions about the company’s performance.

My goal course work is a detailed consideration of the types, tasks and stages of factor analysis, its purpose and relevance of use.

Before we start talking about one of the types of financial analysis - factor analysis, let me remind you what financial analysis is and what its goals are. The financial analysis is a method for assessing the financial condition and performance of an economic entity based on studying the dependence and dynamics of financial reporting indicators.

Financial analysis has several goals: assessing the financial situation; identifying changes in financial condition in space and time; identification of the main factors that caused changes in financial condition; forecast of main trends in financial condition.

As you know, there are the following main types of financial analysis:

· horizontal analysis;

· vertical analysis;

· trend analysis;

· method of financial ratios;

· comparative analysis;

· factor analysis.

Factor analysis- a section of multivariate statistical analysis that combines methods for estimating the dimension of a set of observed variables by studying the structure of covariance or correlation matrices. In other words, the task of the method is to move from a real large number of signs or causes that determine the observed variability to a small number of the most important variables (factors) with minimal loss of information. The method arose and was initially developed in problems of psychology and anthropology (at the turn of the 19th and 20th centuries), but now the scope of its application is much wider.

Basic models of financial analysis

Each type of financial analysis is based on the use of a model that makes it possible to evaluate and analyze the dynamics of the main indicators of the enterprise. There are three main types of models: descriptive, predicative and normative.

Descriptive models also known as descriptive models. They are fundamental for assessing the financial condition of an enterprise. These include: construction of a system of reporting balance sheets, presentation of financial statements in various analytical sections, vertical and horizontal analysis of reporting, a system of analytical coefficients, analytical notes for reporting. All these models are based on the use of accounting information.

At the core vertical analysis lies a different presentation of financial statements - in the form of relative values ​​that characterize the structure of the generalizing total indicators. An obligatory element of the analysis is the dynamic series of these quantities, which makes it possible to track and predict structural changes in the composition of economic assets and the sources of their coverage.

Horizontal analysis allows you to identify trends in changes in individual items or their groups included in the financial statements. This analysis is based on the calculation of the basic growth rates of balance sheet and income statement items.

System of analytical coefficients– the main element of financial analysis, used by various groups of users: managers, analysts, shareholders, investors, creditors, etc. There are dozens of such indicators, divided into several groups according to the main areas of financial analysis:

· liquidity indicators;

· indicators of financial stability;

· indicators of business activity;

· profitability indicators.

Predicative models These are predictive models. They are used to forecast a company's income and its future financial condition. The most common of them are: calculating the point of critical sales volume, constructing forecast financial reports, dynamic analysis models (strictly determined factor models and regression models), situation analysis models.

Normative models. Models of this type allow you to compare the actual results of enterprises with the expected ones calculated according to the budget. These models are used primarily in internal financial analysis. Their essence comes down to the establishment of standards for each cost item for technological processes, types of products, responsibility centers, etc. and to the analysis of deviations of actual data from these standards. The analysis is largely based on the use of strictly deterministic factor models.

As we see, modeling and analysis of factor models occupy an important place in the methodology of financial analysis. Let's consider this aspect in more detail.

Factor analysis, its types and tasks.

The functioning of any socio-economic system (which includes an operating enterprise) occurs in conditions of complex interaction of a complex of internal and external factors. Factor- this is the cause, the driving force of a process or phenomenon, determining its character or one of its main features.

Factor analysis- a methodology for a comprehensive and systematic study and measurement of the impact of factors on the value of performance indicators, a section of multivariate statistical analysis that combines methods for assessing the dimension of many observed variables. In other words, the task of the method is to move from a real large number of signs or causes that determine the observed variability to a small number of the most important variables (factors) with minimal loss of information (methods that are similar in essence, but not in mathematical terms - component analysis, canonical analysis, etc. ). The method arose and was initially developed in problems of psychology and anthropology (at the turn of the 19th and 20th centuries), but now the scope of its application is much wider. The assessment procedure consists of two stages: assessment of the factor structure - the number of factors necessary to explain the correlation between values, and factor loading, and then assessment of the factors themselves based on the results of observation. In short, 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.

Purpose of factor analysis

Factor analysis - definition influence of factors on the result - is one of the strongest methodological solutions in the analysis of the economic activities of companies for decision making. For managers- additional argument, additional "vision angle".

The feasibility of using factor analysis

As you know, you can analyze everything ad infinitum. It is advisable at the first stage to implement an analysis of deviations, and where necessary and justified, to apply the factor analysis method. In many cases, a simple analysis of deviations is enough to understand that the deviation is “critical”, and when it is not at all necessary to know the degree of its influence.

MAIN TASKS OF FACTOR ANALYSIS.

1. Selection of factors determining 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 performance indicators.

4. Modeling the relationships between factors and performance indicators.

5. Calculation of the influence of factors and assessment of the role of each of them in changing the performance indicator.

6. Working with the factor model. Methodology of factor analysis.

However, in practice, factor analysis is rarely used for several reasons:
1) implementation of this method requires some effort and a specific tool (software product);
2) companies have other “eternal” priorities.
It is even better if the factor analysis method is “built-in” into the financial model, and is not abstract application.

In general, the following can be distinguished: main stages of factor analysis :

1. Setting the purpose of the analysis.

2. Selection of factors that determine the performance indicators under study.

3. 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.

4. Determination of the form of dependence between factors and the performance indicator.

5. Modeling the relationships between performance and factor indicators.

6. Calculation of the influence of factors and assessment of the role of each of them in changing the value of the effective indicator.

7. Working with the factor model (its practical use for managing economic processes).

Selection of factors for analysis of a particular indicator is carried out on the basis of theoretical and practical knowledge in a particular 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 business activity analysis (ABA), 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 also represents complex problem in factor analysis, the solution of which requires special knowledge and skills.

Calculation of the influence of factors- the main methodological aspect in ACD. To determine the influence of factors on the final indicators, many methods are used, which will be discussed in more detail below.

The last stage of factor analysis is practical use factor model to calculate reserves for the growth of the effective indicator, to plan and predict its value when the situation changes.

Classification and systematization of factors in the analysis of economic activity.

A factor in economic analysis is actively called active forces, causing positive or negative changes in the state of the object and in the indicators that reflect it. The concept of “factor” is used in economic analysis in 2 meanings:

Condition for carrying out a business transaction;

The reason for the change in the object's state.

FACTORS are the reasons that shape the results of economic and financial activities. Identification and quantitative measurement of the degree of identification of individual factors on changes in the performance indicators of the economic and financial activities of an enterprise is one of the most important tasks economic analysis. The influence of factors is reflected in different ways on changes in the performance indicators of economic activity. The classification of factors will allow us to understand the reasons for changes in the phenomena under study and to 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.

The classification of factors is their distribution into groups depending on common features. It allows you to gain a deeper understanding of the reasons for changes in the phenomena under study, and to more accurately assess the place and role of each factor in the formation of the value of effective indicators.

Classification of factors in economic analysis

1. extensive and intensive

2. permanent and temporary

3. major and minor (Barnholtz). It is customary to use the concept of rank (order) of a factor.

By their nature, factors are divided into natural, socio-economic and production-economic.

Natural factors have a great influence on the performance results in agriculture, in 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, general level 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 final results his activities.

Based on the degree of impact on the results of economic activity, factors are divided into major and minor. The main ones include factors that have a decisive impact on the performance indicator. Those that do not have a decisive impact on the results of economic activity in the current conditions are considered secondary. It should be noted that, depending on the circumstances, the same factor can be both primary and secondary. The ability to identify the main ones from the entire set of factors ensures the correctness of the conclusions based on the results of the analysis.

Factors are divided into internal And external, depending on whether the activities of a given enterprise affect them or not. The analysis focuses on internal factors that the enterprise can influence.

Factors are divided into objective, independent of the will and desires of people, and subjective subject to the influence of the activities of legal entities and individuals.

According to the degree of prevalence, factors are divided into general and specific. Common factors operate in all sectors of the economy. Specific factors operate within a particular industry or a specific enterprise.

In the process of an organization's work, some factors influence the indicator under study continuously throughout the entire time. Such factors are called permanent. Factors whose influence appears periodically are called variables(this is, 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. 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.

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 influence the performance indicator indirectly, with the help of first-level factors, are called second level factors etc.

It is clear that when studying the influence of any group of factors on the work of an enterprise, it is necessary to organize them, that is, to carry out an analysis taking into account their internal and external connections, interaction and subordination. This is achieved through systematization. Systematization is the placement of the phenomena or objects being studied in a certain order, identifying their relationship and subordination.

Systematization of factors in the analysis of economic activity is due to a systematic approach in the analysis of economic activity, and means placing the studied factors in a certain order, identifying their relationship and subordination. One of the ways to systematize factors is to create deterministic factor systems, which means presenting the phenomenon under study in the form of an algebraic sum of a particular or a product of several factors that determine its value and are in functional dependence with it.

Creation factor systems is one of the ways of such systematization of factors. Let's consider the concept of a factor system.

Factor systems

All phenomena and processes of economic activity of enterprises are interdependent. Relationship between economic phenomena is a joint change in two or more phenomena. Among the many forms of regular relationships, an important role is played by cause-and-effect (deterministic), in which one phenomenon gives rise to another.

In the economic activity of an enterprise, some phenomena 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. Many other factors indirectly affect this indicator.

In addition, 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.

Quantitative characteristics interrelated phenomena is carried out using indicators. Indicators characterizing the cause are called factorial (independent); indicators characterizing the consequence are called effective (dependent). The set of factor and resultant characteristics related by cause and effect is called factor system.

Modeling any phenomenon is the construction of a mathematical expression of an existing relationship. Modeling is one of the the most important methods scientific knowledge. There are two types of dependencies studied in the process of factor analysis: functional and stochastic.

A relationship is called functional, or strictly deterministic, if each value of a factor characteristic corresponds to a well-defined non-random value of the resultant characteristic.

A relationship is called stochastic (probabilistic) if each value of a factor characteristic corresponds to a set of values ​​of the resulting characteristic, i.e., a certain statistical distribution.

Model factor system is a mathematical formula that expresses real connections between the analyzed phenomena. IN general view it can be represented like this:

where is the resultant sign;

Factor signs.

Thus, each performance indicator depends on numerous and varied factors. The basis of economic analysis and its section is factor analysis- identify, evaluate and predict the influence of factors on changes in the performance indicator. The more detailed the dependence of the performance indicator on certain factors is studied, the more accurate the results of the analysis and assessment of the quality of the enterprises’ work. Without a deep and comprehensive study of factors, it is impossible to draw reasonable conclusions about the results of activities, identify production reserves, and justify plans and management decisions.

Types of factor analysis

Depending on the type of factor model, there are two main types of factor analysis- deterministic and stochastic.

is a technique for studying the influence of factors whose connection with the effective indicator is functional in nature, that is, when the effective indicator of the factor model is presented in the form of a product, quotient or algebraic sum of factors.

This type of factor analysis is the most common, since, being quite simple to use (compared to stochastic analysis), it allows you to understand the logic of the action of the main factors of enterprise development, quantify their influence, understand which factors and in what proportion it is possible and advisable to change to increase production efficiency.

Deterministic factor analysis has a fairly strict sequence of procedures:

· construction of an economically sound deterministic factor model;

· choosing a method of factor analysis and preparing conditions for its implementation;

· implementation of counting procedures for model analysis;

Basic methods of deterministic factor analysis

· One of the most important methodological factors in ACD is determining the magnitude of the influence of individual factors on the increase in performance indicators. In deterministic factor analysis (DFA), the following methods are used for this: identifying the isolated influence of factors, chain substitution, absolute differences, relative differences, proportional division, integral, logarithm, etc.

· The first three methods are based on the elimination method. Eliminate means to eliminate, reject, exclude the influence of all factors on the value of the effective indicator, except one. This method is based on the fact that all factors change independently of each other: first one changes, and all others remain unchanged, then two change, then three, etc., while the rest remain unchanged. This allows us to determine the influence of each factor on the value of the indicator under study separately.

Stochastic Analysis is a methodology for studying factors whose connection with a performance indicator, unlike a functional one, is incomplete and probabilistic (correlation). The essence of the stochastic method is to measure the influence of stochastic dependencies with uncertain and approximate factors. It is advisable to use the stochastic method for economic research with incomplete (probabilistic) correlation: for example, for marketing problems. 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-labor ratio may be different at different enterprises. This depends on the optimal combination of other factors affecting this indicator.

Stochastic modeling is, to a certain extent, a complement and deepening of deterministic factor analysis. In factor analysis, these models are used for three main reasons:

· it is necessary to study the influence of factors for which it is impossible to build a strictly determined factor model (for example, the level of financial leverage);

· it is necessary to study the influence of complex factors that cannot be combined in the same strictly determined model;

· it is necessary to study the influence of complex factors that cannot be expressed in one quantitative indicator (for example, the level of scientific and technological progress).

In contrast to the strictly deterministic approach, the stochastic approach requires a number of prerequisites for implementation:

a) the presence of a population;

b) a sufficient volume of observations;

c) randomness and independence of observations;

d) homogeneity;

e) the presence of a distribution of characteristics close to normal;

f) the presence of a special mathematical apparatus.

The construction of a stochastic model is carried out in several stages:

· qualitative analysis(setting the purpose of the analysis, defining the population, determining the effective and factor characteristics, choosing the period for which the analysis is carried out, choosing the analysis method);

· preliminary analysis of the simulated population (checking the homogeneity of the population, excluding anomalous observations, clarifying the required sample size, establishing distribution laws for the indicators being studied);

· construction of a stochastic (regression) model (clarification of the list of factors, calculation of estimates of regression equation parameters, enumeration of competing model options);

· assessment of the adequacy of the model (checking the statistical significance of the equation as a whole and its individual parameters, checking the compliance of the formal properties of the estimates with the objectives of the study);

· economic interpretation and practical use of the model (determining the spatio-temporal stability of the constructed relationship, assessing the practical properties of the model).

In addition to dividing into deterministic and stochastic, the following types of factor analysis are distinguished:

o direct and reverse;

o single-stage and multi-stage;

o static and dynamic;

o retrospective and prospective (forecast).

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, . In multi-stage factor analysis, factors are detailed a And b on 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.

Characteristics of the DuPont multifactor model

Developments in the field of factor analysis, which have been carried out since the beginning of the 20th century, have great importance to expand the possibilities of using analytical coefficients for intra-company analysis and management.

First of all, this relates to the development in 1919 of a factor analysis scheme proposed by specialists from the DuPont company (The DuPont System of Analysis). By this time, indicators of return on sales and asset turnover had become quite widespread. However, these indicators were used on their own, without linking them with factors of production. In the DuPont model, for the first time, several indicators were linked together and presented in the form of a triangular structure, at the top of which is the return on total capital ROA as the main indicator characterizing the return received from funds invested in the company's activities, and at the base are two factor indicators - return on sales NPM and TAT resource efficiency.

This model was based on a strictly determined dependence

where is net profit;

The amount of assets of the organization;

- (production volume) sales revenue.

The original representation of the DuPont model is shown in Figure 1:

Figure 1. Schematic of the DuPont model.

In theoretical terms, DuPont specialists were not innovators; they used the original idea of ​​interrelated indicators, first expressed by Alfred Marshall and published by him in 1892 in the book “Elements of Industrial Economics”. Nevertheless, their merit is obvious, since these ideas have not previously been applied in practice.

Subsequently, this model was expanded into a modified factor model, presented in the form of a tree structure, at the top of which is the return on equity (ROE) indicator, and at the base are signs characterizing the factors of the production and financial activities of the enterprise. The main difference between these models is a more detailed identification of factors and a change in priorities relative to the effective indicator. It must be said that the factor analysis models proposed by DuPont specialists remained unclaimed for quite a long time, and only in Lately they began to pay attention.

The mathematical representation of the modified DuPont model is:

where is return on equity;

Emergency- net profit;

A - the amount of the organization's assets;

VR -(production volume) sales revenue.

SK- the organization's own capital.

From the presented model it is clear that return on equity depends on three factors: return on sales, asset turnover and the structure of advanced capital. The significance of the identified factors is explained by the fact that they, in a certain sense, generalize all aspects of the financial and economic activities of the enterprise, its statics and dynamics, in particular the financial statements: the first factor summarizes form No. 2 “Profit and Loss Statement”, the second - the balance sheet asset, the third – balance sheet liability.

Now let's characterize each of the main indicators included in the DuPont model.

Return on equity.

Return on equity is calculated using the formula:

where is the amount of equity at the beginning and end of the period.

In the practice of analysis, many indicators of enterprise performance are used. The return on equity indicator was chosen because it is the most important for the company's shareholders. It characterizes the profit that owners receive from the ruble of funds invested in the enterprise. This coefficient takes into account such important parameters as interest payments for the loan and income tax.

Asset turnover (resource productivity).

The formula for calculating the indicator is:

Where VR– sales revenue for the billing period;

A np, A kp

This indicator can be interpreted in two ways. On the one hand, asset turnover reflects how many times during a period the capital invested in the assets of the enterprise is turned over, i.e. it evaluates the intensity of use of all assets, regardless of the sources of their formation. On the other hand, resource productivity shows how many rubles of revenue an enterprise has per ruble invested in assets. The growth of this indicator indicates an increase in the efficiency of their use.

Sales profitability.

Sales profitability is also one of the the most important indicators efficiency of the company. It is calculated as:

where is the revenue from product sales,

net profit of the enterprise.

This ratio shows how much net profit the company receives from each ruble of products sold. In other words, how much money remains with the enterprise after covering production costs, paying interest on loans and paying taxes. The return on sales indicator characterizes most important aspect the company's activities - the sale of main products, and also allows you to estimate the share of cost in sales.

Return on assets.

The return on assets indicator is calculated using the following formula:

net profit,

A np, A kp– the value of assets at the beginning and end of the period.

Return on assets is an indicator of the efficiency of an enterprise's operational activities. He is the main one production indicator, reflects the efficiency of using invested capital. From the point of view of accounting, this indicator connects the balance sheet and the profit and loss account, that is, the main and investment activities of the enterprise, therefore it is very important for financial management (we will consider the types of activities of the enterprise in detail in the next chapter).

Financial leverage (leverage).

This indicator reflects the structure of capital advanced into the activities of the enterprise. It is calculated as the ratio of the entire advanced capital of the enterprise to the equity capital.

Advance capital,

Equity.

The level of financial leverage can be interpreted, on the one hand, as a characteristic of the financial stability and riskiness of a business, and on the other hand, as an assessment of the efficiency of the enterprise's use of borrowed funds.

Before moving on to factor analysis itself, we will make a number of important reservations regarding the scope of application of the DuPont model.

When analyzing return on equity in the spatiotemporal aspect, it is necessary to take into account three important features of this indicator, which are essential for formulating reasonable conclusions.

The first is related to the temporary aspect of the activities of a commercial organization. The return on sales ratio is determined by the performance of the reporting period; it does not reflect the probable and planned effect of long-term investments. For example, when a business organization makes a transition to new promising technologies or types of products that require large investments, profitability indicators may temporarily decrease. However, if the strategy was chosen correctly, the costs incurred will pay off in the future, and in this case, a decrease in profitability in the reporting period does not mean low efficiency of the enterprise.

The second feature is determined by the problem of risk. One of the indicators of the riskiness of a business is the financial dependence ratio - the higher its value, the more risky the business is from the position of shareholders, investors and creditors.

Thus, it is necessary to take into account the relationships between factors that are not directly reflected in the DuPont model. For example, based only on the mathematical formula of the model, it may seem that an infinite increase in financial leverage will lead to an equally infinite increase in return on equity. However, as the share of borrowed funds in the advanced capital increases, payments for using loans also increase. As a result, net profit decreases and return on equity does not increase. In addition, one cannot ignore the financial risk that accompanies the use of borrowed sources.

The third feature is related to the problem of evaluation. The numerator and denominator of the return on equity ratio are expressed in monetary units of different purchasing power. Profit is a dynamic indicator; it reflects the results of operations and the current level of prices for goods and services, mainly for the past period. Unlike profit, equity capital accumulates over a number of years. It is expressed in an accounting estimate, which may differ greatly from the current market value.

In addition, the accounting estimate of equity does not reflect the future earnings of the enterprise. Not everything can be reflected in the balance sheet; for example, the prestige of a company, a trademark, the latest technologies, and highly qualified personnel do not have an adequate monetary value in the reporting (unless we are talking about the sale of the business as a whole). Thus, the market price of a company's shares may greatly exceed its book value, in which case a high return on equity does not mean a high return on the capital invested in the company. Therefore, the market value of the company should be taken into account.

Conclusion

The purpose of the DuPont model is to identify the factors that determine the efficiency of a business, to assess the degree of their influence and the emerging trends in their change and significance. This model is also used for comparative assessment of the risk of investing or lending to a given enterprise.

All factors in the model, both in terms of significance level and change trends, have industry specific characteristics that the analyst must take into account. Thus, the resource productivity indicator may have a relatively low value in high-tech industries that are characterized by capital intensity; on the contrary, the profitability indicator of economic activity in them will be relatively high. A high value of the financial dependence coefficient can be afforded by firms that have a stable and predictable flow of money for their products. The same applies to enterprises that have a large share of liquid assets (trade and distribution enterprises, banks). Consequently, depending on the industry specifics, as well as the specific financial and economic conditions prevailing at a given enterprise, it can rely on one or another factor to increase the return on equity.

After completing the work, I made the following conclusions.

Factor analysis is one of the strongest methodological solutions in analyzing the economic activities of companies for decision making. The main task, which is solved by various methods of factor analysis, including the method of principal components, is the compression of information, the transition from a set of values ​​according to elementary characteristics with a volume of information to a limited set of elements of a factor mapping matrix or a matrix of latent factor values ​​for each observed object.

Factor analysis methods also make it possible to visualize the structure of the phenomena and processes being studied, which means determining their state and predicting their development. Finally, factor analysis data provide grounds for identifying the object, i.e. solving the problem of image recognition.
Factor analysis methods have properties that are very attractive for their use as part of other statistical methods, most often in correlation and regression analysis, cluster analysis, multidimensional scaling, etc.

LITERATURE:

1. G.V. Savitskaya “Analysis of economic activity” Minsk LLC “New Knowledge”, 2002

2. V.I. Strazhev “Analysis of economic activity in industry”, Mn. Higher school, 2003

3. General and special management: Textbook/General. Ed. A.L. Gaponenko, A.P. Pankrukhin.-M.: Publishing house RAGS, 2001.

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The goal of an enterprise's economic activity is always a certain result, which depends on numerous and varied factors. Obviously, the more detailed the influence of factors on the magnitude of the result is studied, the more accurate and reliable the forecast about the possibility of achieving it will be. Without a deep and comprehensive study of factors, it is impossible to draw informed conclusions about the results of operations, identify production reserves, justify a business plan and make management decisions. Factor analysis, by definition, is a methodology that includes unified methods for measuring (constant and systemic) factor indicators, a comprehensive study of their impact on the value of performance indicators, and the theoretical principles underlying forecasting.

The following are distinguished: types of factor analysis:

– analysis of functional dependencies and correlation analysis (probabilistic dependencies);

– direct and reverse;

– single-stage and multi-stage;

– static and dynamic;

– retrospective and prospective.

Factor analysis of functional dependencies is a technique for studying the influence of factors in the case when the resulting indicator can be presented in the form of a product, quotient or algebraic sum of factors.

Correlation analysis is a technique for studying factors whose connection with an effective indicator is probabilistic (correlation). For example, labor productivity at different enterprises at the same level of capital-labor ratio may also depend on other factors, the impact of which on this indicator is difficult to predict.

In direct factor analysis, the research is conducted from the general to the specific (deductively). Reverse factor analysis carries out research from particular, individual factors to general ones (using the induction method).

Single-stage factor analysis is used to study factors of only one level (one level) of subordination without detailing them into their component parts. For example, y = А·В. In multi-stage factor analysis, factors are detailed A And IN: dividing them into their component elements in order to study interdependencies.

Static factor analysis is used to study the influence of factors on performance indicators as of the corresponding date. Dynamic - is a technique for studying the relationships between factor indicators in dynamics.

Retrospective factor analysis studies the reasons for changes in performance indicators over past periods, while prospective factor analysis predicts the behavior of factors and performance indicators in the future.

The main tasks of factor analysis are the following:

– selection, classification and systematization of factors that influence the studied performance indicators;

– determination of the form of dependence between factors and the performance indicator;

– development (application) of a mathematical model of the relationship between the result and factor indicators;

– calculation of the influence of various factors on the change in the value of the effective indicator and comparison of this influence;

– making a forecast based on a factor model.

From the point of view of impact on the results of financial and economic activities of the enterprise, factors are divided into basic and secondary, internal and external, objective and subjective, general and specific, constant and variable, extensive and intensive.

The main factors include those that have the most significant impact on the result. Others call them minor. It should be noted that, depending on the circumstances, the same factor can be both primary and secondary.

Internal factors are factors that an enterprise can influence. They should be given the most attention. However, external factors (market conditions, inflation processes, conditions of supply of raw materials, materials, their quality, cost, etc.) certainly affect the results of the enterprise. Their study makes it possible to more accurately determine the degree of influence of internal factors and provide a more reliable forecast of production development.

Objective factors do not depend on the will and desires of people (in contracts, the term force majeure is used to refer to these factors; this could be a natural disaster, an unexpected change of political regime, etc.). Unlike objective reasons, subjective reasons depend on the activities of individuals and organizations.

Common factors are characteristic of all sectors of the economy. Specific are those that operate in a particular industry or enterprise. This division of factors allows us to more fully take into account the characteristics of individual enterprises and make a more accurate assessment of their activities.

Constant and variable factors are distinguished by the duration of their impact on production results . Constant factors influence the phenomenon under study continuously throughout the entire period under study (reporting period, production cycle, product life, etc.). The impact of variable factors is one-time, irregular.

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 qualitative changes in the production process, for example, an increase in crop yields as a result of the use of new types of fertilizers.

Factors are also divided into quantitative and qualitative, complex and simple, direct and indirect. Quantitative factors, by definition, can be measured (number of workers, equipment, raw materials, labor productivity, etc.). But often the process of measuring or searching for information is difficult, and then the influence of individual factors is characterized qualitatively (more - less, better - worse).

Most of the factors studied in the analysis 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 (single-element). An example of a complex factor is labor productivity, and a simple one is the number of working days in the reporting period.

Factors that have a direct impact on the performance indicator are called direct (factors of direct action). Indirect ones influence through the mediation of other factors. Depending on the degree of indirect influence, factors of the first, second, third and subsequent levels of subordination are distinguished. Thus, direct action factors — first level factors. Factors that determine the performance indicator indirectly, using first-level factors, are called second level factors etc.

Any factor analysis of indicators begins with modeling a multifactor model. The essence of building a model is to create a specific mathematical relationship between factors.

When modeling functional factor systems, a number of requirements must be met.

1. Factors included in the model must actually exist and have a specific physical meaning.

2. Factors that are included in the system of factor analysis of indicators must have a cause-and-effect relationship with the indicator being studied.

3. The factor model must provide measurement of the influence of a specific factor on the overall result.

In factor analysis of indicators, the following types of the most common models are used.

1. When the resultant indicator is obtained as an algebraic sum or the difference of the resulting factors, apply additive models, for example:

,

where is the profit from product sales,

- revenues from sales,

– production cost of goods sold,

– business expenses,

– administrative expenses.

Multiplicative models are used when the resulting indicator is obtained as a product of several resulting factors:


,


where is return on assets,


– profitability of sales,


– return on assets,


– the average value of the organization’s assets for the reporting year.


3. When the effective indicator is obtained by dividing one factor by another, apply multiples models:


Various combinations of the above models give mixed or combined models:


;


;


etc.


In the practice of economic analysis, there are several ways to model multifactor models: lengthening, formal decomposition, expansion, reduction and dismemberment of one or several factor indicators into component elements.


For example, using the expansion method, you can build a three-factor model of the organization’s return on assets as follows:


;


,


where is the organization’s equity capital turnover,


– independence coefficient or the share of equity capital in the total assets of the organization,


– the average cost of the organization’s equity capital for the reporting period.


Thus, we have obtained a three-factor multiplicative model of the organization's return on assets. This model is widely known in the economic literature as the Dupont model. Considering this model, we can say that the profitability of an organization’s assets is influenced by the return on sales, equity turnover and the share of equity in the total assets of the organization.


Now consider the following return on assets model:


=;


where is the share of revenue per 1 rub. full cost of production,


– share current assets in the formation of assets,


– share of inventories in the formation of current assets,


– inventory turnover.


The first factor of this model speaks about pricing policy organization, it shows the basic markup that is included directly in the price of the products sold.


The second and third factors show the structure of assets and current assets, the optimal value of which makes it possible to save working capital.


The fourth factor is determined by the volume of production and sales of products and speaks of the efficiency of use of inventories; physically it expresses the number of revolutions that inventories make during the reporting year.


Equity method used when it is difficult to establish the dependence of the analyzed indicator on private indicators. The method is that the deviation according to the general indicator is proportionally distributed among the individual factors under the influence of which it occurred. For example, you can calculate the impact of changes in book profit on the level of profitability using the formula:


R i = R·( i / b) ,


where  R i- change in the level of profitability due to an increase in profit under the influence of a factor i, %;


R-change in the level of profitability due to changes in balance sheet profit,%;


 b - change in balance sheet profit, rub.;


i- change in balance sheet profit due to the factor i.


Chain substitution method allows you to measure the influence of individual factors on the result of their interaction - generalizing ( target) indicator, calculate deviations of actual indicators from standard (planned) indicators.


Substitution is the replacement of a basic or standard value of a particular indicator with an actual one. Chain substitutions are sequential replacements of the basic values ​​of particular indicators included in the calculation formula with the actual values ​​of these indicators. Then these influences (the influence of the replacement made on the change in the value of the general indicator being studied) are compared with each other. The number of substitutions is equal to the number of partial indicators included in the calculation formula.


The method of chain substitutions consists in determining a number of intermediate values ​​of the generalizing indicator by sequentially replacing the basic values ​​of the factors with the reporting ones. This method is based on elimination. Eliminate means to eliminate, exclude the influence of all factors on the value of the effective indicator, except one. Moreover, based on the fact that all factors change independently of each other, i.e. First, one factor changes, and all the others remain unchanged. then two change while the others remain unchanged, etc.


In general, the application of the chain production method can be described as follows:





where a 0, b 0, c 0 are the basic values ​​of factors influencing the general indicator y;


a 1 , b 1 , c 1 —
actual values ​​of factors;


y a , y b , —
intermediate changes
the resulting indicator associated with changes in factors a, b, respectively.


The total change  y=y 1 –y 0 consists of the sum of changes in the resulting indicator due to changes in each factor with fixed values ​​of the other factors:


The algorithm of the chain substitution method can be demonstrated by the example of calculating the impact of changes in the values ​​of partial indicators on the value of the indicator, presented in the form of the following calculation formula: F = a· b· c· d.


Then the base value F will be equal F 0 = a 0 · b 0 · c 0 · d 0 ,


and the actual one: F 1 = a 1 · b 1 · c 1 · d 1 .


Total deviation of the actual indicator from the basic indicator  F (F=F 1 –F 0) is obviously equal to the sum of deviations obtained under the influence of changes in particular indicators:


F = F 1 +F 2 +F 3 +F 4 .


And changes in private indicators are calculated by successive substitutions into the formula for calculating the indicator F actual parameter values a, b, c, d instead of basic ones:


The calculation is checked by comparing the balance of deviations, i.e. the total deviation of the actual indicator from the basic indicator should be equal to the sum of deviations under the influence of changes in private indicators:


F 1 –F 0 = F 1 +F 2 +F 3 +F 4 .


Advantages this method: versatility of application, ease of calculations.


The disadvantage of the method is that, depending on the chosen order of factor replacement, the results of factor decomposition have different meanings. This is due to the fact that as a result of applying this method, a certain indecomposable residue is formed, which is added to the magnitude of the influence of the last factor. In practice, the accuracy of factor assessment is neglected, highlighting the relative importance of the influence of one or another factor. However, there are certain rules, defining the substitution sequence:

if there are quantitative and qualitative indicators in the factor model, the change in quantitative factors is considered first;


if the model is represented by several quantitative and qualitative indicators, the substitution sequence is determined by logical analysis.


In analysis, quantitative factors are understood as those that express the quantitative certainty of phenomena and can be obtained by direct accounting (number of workers, machines, raw materials, etc.).


Qualitative factors determine the internal qualities, signs and characteristics of the phenomena being studied (labor productivity, product quality, average working hours, etc.).


A variation of the method of chain substitutions is the method of calculation using absolute differences. The target function in this case, as in the previous example, is presented in the form of a multiplicative model. The change in the value of each factor is determined in comparison with the base value, for example, the planned one. Then these differences are multiplied by the remaining partial indicators - the factors of the multiplicative model. But, note, when moving from one factor to another, a different value of the multiplier is taken into account. The factors that appear after the factor (on the right) by which the difference is calculated remain in the value of the base period, and all those remaining before it (on the left) are taken in the values ​​of the reporting period.


The absolute difference method is a modification of the chain substitution method. The change in the effective indicator due to each factor using the method of differences is defined as the product of the deviation of the factor being studied by the basic or reporting value of another factor, depending on the selected substitution sequence:





We will show this using the example of the influence of individual factors on the amount of materials costs TS m, which are formed under the influence of three factors: volume of production in physical terms Q, norms of material consumption per accounting unit of production m and prices for materials Pm.


TS m = Q· m· Pm.


First, the change in each factor compared to the plan is calculated:


change in production volume  Q= Q 0 – Q 1 ;


change in material consumption rates per accounting unit  m = m 0 – m 1 ;


change in price per unit of material  Pm = Pm 1 – Pm 0 .


Next, the influence of individual factors on the general indicator is determined, i.e. the amount of costs for materials. In this case, the partial indicators that stand before the indicator by which the difference is calculated are left in their actual value, and all those following it are left in the basic value.


In this case, the impact of changes in production volume  Q the amount of materials costs will be:


TS mQ = Q· m 0 · Pm 0 ;


influence of changes in material consumption rates  TS mm:


TS mm = Q 1 · m· Pm 0 ;


impact of changes in prices for materials  TS mp:


TS mp = Q 1 · m 1 · Pm.


The total deviation of the amount of costs for materials will be equal to the sum of the deviations of the influence of individual factors, i.e.


TS m = TS mQ + TS mm + TS mp.


However, in practice there are more often situations when one can only assume the existence of a functional dependence (for example, the dependence of revenue ( TR) from the number of products produced and sold ( Q): TR = TR(Q)). To test this assumption, use regression analysis by which a function is selected a certain type (F r(Q)). Then, on the set of function definition (on the set of values ​​of the factor indicator), the set of function values ​​is calculated.


The method of relative differences is used to measure the influence of factors on the growth of an effective indicator in multiplicative and mixed models of the form y = (a – c) . With. It is used in cases where the source data contains previously determined relative deviations of factor indicators in percentages.


For multiplicative models like y = a . V . The analysis technique is as follows:


find the relative deviation of each factor indicator:





determine the deviation of the performance indicator at due to each factor





The integral method allows you to avoid the disadvantages inherent in the chain substitution method and does not require the use of techniques for distributing the indecomposable remainder among factors, because it has a logarithmic law of redistribution of factor loads. The integral method makes it possible to achieve a complete decomposition of the effective indicator into factors and is universal in nature, i.e. applicable to multiplicative, multiple and mixed models. Calculation operation definite integral is solved using a PC and comes down to constructing integrands that depend on the type of function or model of the factor system.


You can also use already formed working formulas given in specialized literature:


1. Model view:





2. View model :





3. View model:





4. View model:





A comprehensive analysis of financial condition involves a broad and full research all factors that influence or may influence the final financial results of the organization, which, ultimately, are the main goal of the organization.


The results of the analysis must be used to make the correct management decisions administration of the organization and informed investment decisions by shareholders-owners.


TASK 2


It is known that during the reporting period the average number of workers on the payroll increased from 500 to 520 people, the average number of hours worked per working day - from 7.4 to 7.5 hours; the average number of days worked by workers per year decreased from 290 to 280 days; the average hourly output of a worker decreased from 26.5 rubles to 23 rubles. The volume of production decreased from 28434.5 tr. up to 25116 tr. Using the method of relative differences, evaluate the influence of factors on changes in production volume. Draw reasoned conclusions.


SOLUTION


Relative difference method used to measure the influence of factors on the growth of a performance indicator only in multiplicative and additive-multiplicative models.


Table 1


Initial data for calculation


Index	Designation	Base year	Reporting year	Deviations (+;-)
Average number of workers, people.
Average number of hours worked by one worker per day, hours.
Average number of days worked by a worker per year, days
Average hourly output, rub.		26,5
Product output volume, t.r.	VP	28434,5	25116	3318,5

We have a model of the form


VP = H*t*N*F,


In this case, the change in the performance indicator is determined as follows





According to this rule, to calculate the influence of the first factor, it is necessary to multiply the basic (planned) value of the effective indicator by the relative increase of the first factor, expressed as a decimal fraction.


To calculate the influence of the second factor, you need to add the change in it due to the first factor to the planned (basic) value of the effective indicator and then multiply the resulting amount by the relative increase in the Second factor.


The influence of the third factor is determined similarly: to planned value of the effective indicator, it is necessary to add its growth due to the first and second factors and multiply the resulting amount by the relative growth of the third factor.


The influence of the quadruple factor is similar





Let’s summarize the factors that influenced the formation of revenue in the reporting year:


increase in the number of workers 1137.38 thousand rubles.


increasing the number of hours worked by one worker


per day 399.62 tr.


changes in the number of working days -1033.5 tr.


Changes in average hourly output -3821.95 tr.


Total -3318.45 t.r.


Thus, based on the method of relative differences, it was found that the total influence of all factors amounted to -3318.45 tr, which coincides with the absolute dynamics of the volume of production according to the conditions of the problem. A small discrepancy is determined by the degree of rounding in the calculations. The growth in average payroll workers by 20 people in the amount of 1137.8 tr, a slight increase in the working day of one worker by 0.1 hour led to an increase in output by 399.62 tr. Bad influence had a reduction in the average hourly work per worker by 3.5 rubles. per hour, which resulted in a decrease in production volume by -3821.5 tr. A decrease in the average number of days worked by one worker per year by 10 days led to a decrease in production volumes by -1033.5 tr.


TASK 3


Using the economic information of your enterprise, assess its financial stability based on the calculation of relative indicators.


SOLUTION


Joint-stock company "KRAITEKHSNAB", registered by the Registration Chamber of the Krasnodar City Hall No. 10952 dated May 14, 1999, OGRN 1022301987278, hereinafter referred to as the "Company", is a closed joint-stock company.


The Company is a legal entity and operates on the basis of the Charter and legislation of the Russian Federation. Society has round stamp, containing its full corporate name in Russian and an indication of its location, stamps and forms with its name, its own emblem, as well as a trademark registered in the prescribed manner and other means of visual identification.


Full corporate name of the Company in Russian:
Closed Joint-Stock Company"KRAITECHSNAB". The abbreviated corporate name of the Company in Russian is ZAO KRAITECHSNAB.


Location (mailing address) of the Company: 350021, Russian Federation, Krasnodar region, Krasnodar, Karasunsky administrative District, st. Tramway, 25.


Closed joint stock company "KRAITECHSNAB" was created without any limitation on the period of activity.


The main subject of the Company's activity is trade and purchasing activities, intermediary, brokerage.


Let us analyze the financial stability indicators of the organization under study (Table 2).


table 2


Analysis of financial stability indicators of Kraytekhsnab CJSC in absolute terms


Indicators	2003	2004	2005	2005 to 2003
				(+,-)	Growth rate, %
1. Sources of own funds	7371212,4	6508475,4	7713483,3	342 270,9	1004,6
2. Non-current assets	1339265,0	1320240,0	1301215,0	38 050,0	97,2
3. Sources of own working capital for the formation of reserves and costs	6031947,4	5188235,4	6412268,4	380 321,0	1006,3
4. Long-term loans and borrowings
5. Sources of own funds, adjusted for the amount of long-term borrowed funds	6031947,4	5188235,4	6412268,4	380 321,0	106,3
6. Short-term credit and borrowed funds	1500000,0	2000000,0	1500000,0
7. The total amount of sources of funds, taking into account long-term and short-term borrowed funds	7531947,4	7188235,4	7912268,4	380 321,0	105,0
8. The amount of inventories and costs circulating in the balance sheet asset	9784805,7	10289636,4	11152558,8	1367753,1	114,0

End of table 2


Indicators	2003	2004	2005	2005 to 2003
				(+,-)	Growth rate, %
9. Excess sources of own working capital	3752858,3	5101401,1	4740290,4	987432,2	126,3
10. Excess of sources of own funds and long-term borrowed sources	3752858,3	5101401,1	4740290,4	987432,2	126,3
11. Surplus of the total value of all sources for the formation of reserves and costs	2252858,3	3101401,1	3240290,4	987 432,2	143,8
12. Three complex indicator (S) of the financial situation	(0,0,0)	(0,0,0)	(0,0,0)

Analyzing the type of financial stability of an enterprise over time, a noticeable decrease in the financial stability of the enterprise is observed.


As can be seen from Table 2, both in 2003, and in 2004, and in 2005, the financial stability of Kraytekhsnab CJSC according to the 3-complex indicator of financial stability can be characterized as “Crisis-unstable state of the enterprise”, since the enterprise does not have enough funds to form reserves and costs to carry out current activities.


Let's calculate the financial stability coefficients of Kraytekhsnab CJSC (Table 3).


Table 3


Financial stability ratios of Kraytekhsnab CJSC


Indicators	2003	2004	2005	(+,-)
				2004 2003	2005 to 2004
Autonomy coefficient	0,44	0,37	0,30	0,06	0,08
Debt to equity ratio (financial leverage)	1,28	1,67	2,34	0,39	0,67
Ratio of mobile and immobilized assets	11,56	13,32	18,79	1,76	5,47
Debt to equity ratio	0,78	0,60	0,43	0,18	0,17
Maneuverability coefficient	0,82	0,80	0,83	0,02	0,03
Inventory and cost coverage ratio with own funds	0,62	0,50	0,57	0,11	0,07
Industrial property ratio	0,66	0,61	0,48	0,05	0,13
Short-term debt ratio, %	15,9	18,4			10,1
Accounts payable ratio, %	84,1	81,6	91,7		10,1

An analysis of financial stability by relative indicators presented in Table 3 suggests that, according to the indicators presented in the table, compared with the base period (2003), the situation at Kraytekhsnab CJSC generally worsened in 2004 and improved slightly in the reporting year 2005 G.


The indicator “Autonomy coefficient” for the period from 2003 to 2004 decreased by -0.06 and in 2004 amounted to 0.37. This is below the standard value (0.5) at which borrowed capital can be compensated by the property of the enterprise. The indicator “Autonomy coefficient” for the period from 2004 to 2005 decreased by -0.08 and in 2005 amounted to 0.30. This is also below the standard value (0.5) at which borrowed capital can be compensated by the property of the enterprise.


The indicator “Ratio of debt and equity” (financial leverage) increased by 0.39 from 2003 to 2004 and amounted to 1.67 in 2004. The indicator for 2004 to 2005 increased by 0.67 and in 2005 amounted to 2.34. The more this ratio exceeds 1, the greater the enterprise's dependence on borrowed funds. The acceptable level is often determined by the operating conditions of each enterprise, primarily by the rate of turnover of working capital. Therefore, it is additionally necessary to determine the rate of turnover of inventories and receivables for the analyzed period. If accounts receivable turn over faster than working capital, which means a fairly high intensity of cash flow to the enterprise, i.e. the result is an increase in own funds. Therefore, with a high turnover of tangible working capital and an even higher turnover of accounts receivable, the ratio of equity and borrowed funds can greatly exceed 1.


The indicator “Ratio of mobile and immobilized assets” increased by 1.76 from 2003 to 2004 and amounted to 13.32 in 2004. The indicator for 2004 to 2005 increased by 5.47 and in 2005 amounted to 18.79. The standard value is specific to each individual industry, but all other things being equal, an increase in the coefficient is a positive trend.


Indicator "Maneuverability coefficient", for the period 2003 - 2004. decreased by -0.02 and at the end of Dec. 2004 was 0.80. This is higher than the standard value (0.5). The indicator for the period 2004 to 2005 increased by 0.03 and in 2005 amounted to 0.83. This is higher than the standard value (0.5). The agility coefficient characterizes what share of sources of own funds is in mobile form. The normative value of the indicator depends on the nature of the enterprise’s activities: in capital-intensive industries its normal level should be lower than in material-intensive ones. At the end of the analyzed period, Kraytekhsnab CJSC has a light asset structure. The share of fixed assets in the balance sheet currency is less than 40.0%. Thus, the enterprise cannot be classified as a capital-intensive industry.


Indicator “Coefficient of coverage of inventories and costs with own funds”, for 2003 – 2004. decreased by -0.11 and in 2004 amounted to 0.50. The indicator for the period 2004–2005 increased by 0.07 and in 2005 amounted to 0.57. This is lower than the standard value (0.6 - 0.8), as in 2003, 2004 and 2005. The company lacks its own funds for the formation of reserves and costs, as shown by the analysis of financial stability indicators in absolute terms.


BIBLIOGRAPHY

1. The procedure for monitoring the financial condition of organizations and recording their solvency. Federal Service of Russia for Insolvency and Financial Recovery: Order No. 13-r dated March 31, 1999 // Economics and Life. 1999. No. 22.
   

2. Bakanov M.I., Sheremet A.D. Theory of economic analysis. –M.: Finance and Statistics, 2006.
   ASSESSMENT OF THE ECONOMIC INDICATORS OF THE ACTIVITY OF A TRADING ENTERPRISE USING THE EXAMPLE OF THE MAIN INDICATORS OF THE ENTERPRISE'S ACTIVITY SHOW THE USE OF 6 PARTICULAR METHODS AND TECHNIQUES OF ECONOMIC ANALYSIS Financial condition trade organization and assessment of economic indicators

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