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

Under factor analysis refers to the methodology of complex and systematic study and measurement of the impact of factors on the magnitude of performance indicators.

In general, the following main stages (tasks) factor analysis:

Setting the goal of the analysis.

Selection of factors that determine the studied performance indicators.

Classification and systematization of factors in order to provide an integrated and systematic approach to the study of their impact on the results of economic activity.

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

Modeling the relationship between performance and factor indicators.

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

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

In other words, method task- transition from the real a large number signs or reasons 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 terms of mathematical apparatus - component analysis, canonical analysis, etc.).

The method arose and was originally developed in the problems of psychology and anthropology (at the turn of the 19th and 20th centuries), but now the scope of its application is much wider.

Purpose of factor analysis

Factor analysis- determination of the 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 - an additional argument, an additional "point of view".

The feasibility of using factor analysis

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

The factors are divided into internal and external, depending on whether they are affected by the activities of the enterprise or not. The analysis focuses on internal factors that the company can influence.

The factors are divided into objective, independent of the will and desires of people, and subjective, affected by the activities of legal entities and individuals.

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

Types of factor analysis

Exist the following types factor analysis:

1) Deterministic (functional) - the effective indicator is presented as a product, private or algebraic sum of factors.

2) Stochastic (correlation) - the relationship between the performance and factor indicators is incomplete or probabilistic.

3) Direct (deductive) - from the general to the particular.

4) Inverse (inductive) - from the particular to the general.

5) Single-stage and multi-stage.

6) Static and dynamic.

7) Retrospective and prospective.

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

Deterministic factor analysis is a methodology for studying the influence of factors whose relationship with the performance indicator is functional, that is, when the performance indicator of the factor model is presented as a product, private or algebraic sum of factors.

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

Deterministic factor analysis has a fairly rigid sequence of procedures performed:

1. building an economically sound deterministic factor model;

2. choice of method of factor analysis and preparation of conditions for its implementation;

3. implementation of counting procedures for model analysis;

Basic methods of deterministic factor analysis

Chain substitution method; Method of absolute differences; Relative difference method; Integral method; Logarithm method.

Stochastic analysis is a methodology for studying factors whose relationship with the performance indicator, in contrast to the functional one, is incomplete, probabilistic (correlation). The essence of the stochastic method is the measurement of the influence of stochastic dependencies with uncertain and approximate factors. Stochastic method it is advisable to use for economic research with incomplete (probabilistic) correlation: for example, for marketing tasks. If with a functional (full) dependence, a corresponding change in the function always occurs with a change in the argument, then with a correlation, 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 not be the same in different enterprises. It depends on the optimal combination of other factors affecting this indicator.

Stochastic modeling is, to a certain extent, an addition and extension of deterministic factor analysis. In factor analysis, these models are used in three main ways. reasons:

It is necessary to study the influence of factors that cannot be used to build a rigidly deterministic 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 rigidly deterministic 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).

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 for the corresponding date. Another type is a methodology for studying cause-and-effect relationships in dynamics.

Finally, factor analysis can be retrospective which studies the reasons for the increase in performance indicators for past periods, and promising which examines the behavior of factors and performance indicators in the future.

Factor analysis can be single-stage and multi-stage. The first type is used to study the factors of only one level (one stage) of subordination without detailing them into their constituent parts. For example, . In multistage factor analysis, the factors a and b are detailed into their constituent elements in order to study their behavior. Detailing the factors can be continued further. In this case, the influence of factors of different levels of subordination is studied.

It is also necessary to distinguish between static and dynamic factor analysis.. The first type is used when studying the influence of factors on performance indicators for the corresponding date. Another type is a methodology for studying cause-and-effect relationships in dynamics.

aim economic activity enterprise is always a certain result, which depends on many and varied factors. It is obvious that 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 the factors, it is impossible to draw reasonable conclusions about the results of activities, identify production reserves, justify a business plan and make a management decision. 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 magnitude of performance indicators, and theoretical principles underlying forecasting.

There are the following 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 functional dependencies is a technique for studying the influence of factors in the case when the effective indicator can be represented as a product, private or algebraic sum of factors.

Correlation analysis is a technique for studying factors whose relationship with the performance indicator is probabilistic (correlation). For example, labor productivity at different enterprises with 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 study is conducted from the general to the particular (deductively). Reverse factor analysis carries out research from private, individual factors to general ones (by induction).

Single-stage factor analysis is used to study the factors of only one level (one stage) of subordination without their detailing into component parts. For example, y \u003d A B. In multistage factor analysis, the factors are detailed BUT and AT: dividing them into their constituent elements in order to study interdependencies.

Static factor analysis is used when studying the influence of factors on performance indicators for the corresponding date. Dynamic - is a technique for studying the relationship of factor indicators in dynamics.

Retrospective factor analysis studies the causes of changes in performance indicators for past periods, prospective - 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 affect the studied performance indicators;

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

– development (application) mathematical model relationships 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 factorial model.

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

The main ones are the factors that have the most noticeable effect on the result. Others are called secondary. It should be noted that, depending on the circumstances, the same factor can be both primary and secondary.

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

Objective factors do not depend on the will and desires of people (in contracts, these factors are referred to as force majeure; it can be a natural disaster, an unexpected change of political regime, etc.). Unlike objective, subjective causes depend on the activities of individuals and organizations.

General factors are characteristic of all sectors of the economy. Specific are those that operate in a particular industry or enterprise. Such a division of factors makes it possible to take into account the characteristics of individual enterprises more fully and to make a more accurate assessment of their activities.

Fixed and variable factors are distinguished by the period of impact on the results of production . Constant factors have an impact on 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 those that are associated with a quantitative, rather than qualitative, increase in the result 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 are not decomposed into component parts. In this regard, the 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 direct action). Indirect ones influence through the mediation of other factors. Depending on the degree of mediation of 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, with the help of first-level factors, are called second level factors etc.

Any factorial analysis of indicators begins with the modeling of a multifactorial 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 observed.

1. The 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 causal relationship with the indicator under study.

3. The factor model should provide a measure of the influence of a particular factor on the overall result.

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

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

,

where is the profit from the sale of products,

- revenues from sales,

- production cost of goods sold,

- business expenses

- administrative expenses.

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


,


where - return on assets,


- return on sales


- return on assets,


- the average value of the organization's assets for the reporting year.


3. When the performance 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 multifactorial models: lengthening, formal decomposition, expansion, reduction and division of one or more factor indicators into constituent elements.


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


;


,


where is turnover equity organizations,


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


is the average cost of the organization's equity capital for reporting period.


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


Now consider the following return on assets model:


=;


where - the share of revenue attributable to 1 rub. full cost of production


– share current assets in the formation of assets,


- the share of stocks in the formation of current assets,


- inventory turnover.


The first factor of this model speaks about the pricing policy of the organization, it shows the basic margin, which is directly embedded in the price of 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 magnitude of output and sales of products and speaks of the efficiency of the use of inventories; physically, it expresses the number of turnovers that stocks make in the reporting year.


Equity method is used when it is difficult to establish the dependence of the analyzed indicator on private indicators. The method lies in the fact that the deviation according to the generalizing indicator is proportionally distributed among the individual factors under the influence of which it occurred. For example, you can calculate the impact of a change in balance sheet 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 profits under the influence of the 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.


Method of chain substitutions 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).


Substitution is the replacement of the basic or normative value of a particular indicator with an actual one. Chain substitutions are successive replacements of the base values ​​of particular indicators included in the calculation formula with the actual values ​​of these indicators. Then these influences (the influence of the replacement on the change in the value of the studied generalizing indicator) 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 successively replacing the basic values ​​of the factors with the reporting ones. This method is based on elimination. To eliminate means to eliminate, exclude the influence of all factors on the value of the effective indicator, except for one. At the same time, 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 rest remain unchanged, and so on.


AT general view The application of the chain setting method can be described as follows:





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


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


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


The total change  y=y 1 -y 0 is the sum of the 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 effect 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 to F 0 = a 0 · b 0 · c 0 · d 0 ,


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


General deviation of the actual indicator from the baseline  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 in the formula for calculating the indicator F actual parameter values a, b, c, d instead of basic


The verification of the calculation is carried out by comparing the balance of deviations, i.e. the total deviation of the actual indicator from the baseline should be equal to the sum of deviations under the influence of changes in particular indicators:


F 1 –F 0 = F 1 +F 2 +F 3 +F 4 .


Advantages this method: universality of application, simplicity of calculations.


The disadvantage of the method is that, depending on the chosen order of factor replacement, the results of the factor expansion 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 assessing factors is neglected, highlighting the relative importance of the influence of one or another factor. However, there are certain rules that determine the sequence of substitution:

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


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


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


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


A variation of the method of chain substitutions is the method of calculation using absolute differences. In this case, the objective function, as in the previous example, is presented as 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 other partial indicators - multipliers of the multiplicative model. But, we note, when moving from one factor to another, a different value of the multiplier is taken into account. The multipliers after the factor (on the right), by which the difference is calculated, remain in the value of the base period, and all 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 by the difference method is defined as the product of the deviation of the studied factor by the base or reporting value of another factor, depending on the selected substitution sequence:





Let's show this on the example of the influence of individual factors on the amount of material costs TS m, which are formed under the influence of three factors: the volume of output in physical terms Q, consumption rates of materials per accounting unit of production m and material prices Pm.


TS m = Q· m· Pm.


First, the change in each factor in comparison with the plan is calculated:


change in output  Q= Q 0 – Q 1 ;


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


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


Next, the influence of individual factors on the generalizing indicator is determined, i.e. the cost of materials. At the same time, the partial indicators that precede the indicator by which the difference is calculated are left in their actual value, and all those following it are in the base value.


In this case, the effect of a change in the volume of output  Q the cost of materials will be:


TS mQ = Q· m 0 · Pm 0 ;


the impact of changing material consumption rates  TS mm:


TS mm = Q 1  m· Pm 0 ;


the impact of price changes on materials  ts mp:


ts mp = Q one · m 1  Pm.


The total deviation of the amount of material costs 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 situations where one can only assume the presence functional dependence(for example, the dependence of revenue ( TR) from the number of produced and sold products ( Q): TR = TR(Q)). To test this assumption, use regressive analysis, with the help of which a function of a certain type is chosen ( F r(Q)). Then, on the set of function definitions (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 the effective indicator in multiplicative and mixed models of the form y \u003d (a - c) . with. It is used in cases where the initial data contain previously defined relative deviations of factorial indicators in percent.


For multiplicative models like y = a . in . with the analysis technique is as follows:


find the relative deviation of each factor indicator:





determine the deviation of the effective indicator at for each factor





The integral method makes it possible to avoid the disadvantages inherent in the chain substitution method and does not require the use of methods for distributing the irreducible remainder over factors, since it has a logarithmic law of redistribution of factor loadings. The integral method allows you to achieve a complete decomposition of the effective indicator by factors and is universal in nature, i.e. applicable to multiplicative, multiple, and mixed models. The operation of calculating a definite integral is solved with the help of a PC and is reduced to the construction of integrands that depend on the type of function or model of the factorial system.


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


1. View model:





2. View model :





3. View Model :





4. View Model :





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


The results of the analysis should be used to make the right management decisions by the administration of the organization and reasonable 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 worker per day - from 7.4 to 7.5 hours; the average number of days worked by a worker per year was reduced from 290 to 280 days; the average hourly output of a worker decreased from 26.5 rubles to 23 rubles. The volume of output decreased from 28434.5 tr. up to 25116 tr. Using the method of relative differences, evaluate the influence of factors on the change in the volume of output. Draw reasoned conclusions.


DECISION


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


Table 1


Initial data for calculation


Indicator	Designation	Base year	Reporting year	Deviations (+;-)
Average payroll number of workers, pers.
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
Output volume, tr.	VP	28434,5	25116	3318,5

We have a view model


VP \u003d 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 base (planned) value of the effective indicator by the relative growth of the first factor, expressed as a decimal fraction.


To calculate the influence of the second factor, it is necessary to add the change 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 Proth factor.


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


Similarly, the influence of the fourth factor





Let's summarize the factors that contributed to the formation of revenue in the reporting year:


increase in the number of workers 1137.38 t.


increasing the number of hours worked per worker


per day 399.62 t.


changes in the number of working days -1033.5 t.


Changes in average hourly output -3821.95 tr.


Total -3318.45 thousand rubles


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 output according to the condition of the problem. A slight discrepancy is determined by the degree of rounding in the calculations. The growth of the average payroll workers for 20 people in the amount of 1137.8 tr, a slight increase in the working day of one worker by 0.1 hours led to an increase in output by 399.62 tr. A negative impact was exerted by a decrease in the average hourly work of one worker by 3.5 rubles. per hour, which resulted in a decrease in output by -3821.5 tr. The decrease in the average number of days worked by one worker per year by 10 days led to a decrease in output by -1033.5 tr.


TASK 3


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


DECISION


Joint Stock Company "KRAITEHSNAB", registered by the Registration Chamber of the Mayor's Office of Krasnodar No. 10952 dated May 14, 1999, PSRN 1022301987278, hereinafter referred to as the "Company", is a closed joint stock company.


Society is legal entity and operates on the basis of the Charter and the legislation of the Russian Federation. The Company has a round seal containing its full company 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"KRAITEHSNAB". Abbreviated corporate name of the Company in Russian: CJSC KRAITEHSNAB.


Location (postal address) of the Company: 350021, Russian Federation, Krasnodar region, Krasnodar, Karasunsky administrative district, st. Tram, 25.


Closed Joint Stock Company "KRAITEHSNAB" was established without limitation of the period of activity.


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


Let's analyze the indicators of financial stability of the organization under study (table 2).


table 2


Analysis of indicators of financial stability of CJSC "Kraitekhsnab" 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 stocks 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 borrowings	6031947,4	5188235,4	6412268,4	380 321,0	106,3
6. Short-term loans and borrowings	1500000,0	2000000,0	1500000,0
7. The total value of sources of funds, taking into account long-term and short-term borrowings	7531947,4	7188235,4	7912268,4	380 321,0	105,0
8. The amount of stocks and costs circulating in the asset balance	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. Surplus 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)

When analyzing the type of financial stability of an enterprise in dynamics, a decrease in the financial stability of an enterprise is noticeable.


As can be seen from Table 2, in 2003, and in 2004, and in 2005, the financial stability of CJSC "Kraitekhsnab" in terms of a 3-complex indicator of financial stability can be characterized as "Crisis-unstable state of the enterprise", since the enterprise does not have enough funds for the formation of stocks and costs for the implementation of current activities.


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


Table 3


Financial stability ratios of CJSC "Kraitekhsnab"


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
The ratio of mobile and immobilized means	11,56	13,32	18,79	1,76	5,47
The coefficient of the ratio of own and borrowed funds	0,78	0,60	0,43	0,18	0,17
Agility factor	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

The analysis of financial stability in terms of relative indicators, presented in Table 3, indicates that, according to the indicators presented in the table, compared with the base period (2003), the situation at CJSC "Kraitekhsnab" as a whole worsened in 2004 and slightly improved in the reporting 2005 G.


The indicator "Coefficient of autonomy" for the period from 2003 to 2004 decreased by -0.06 and in 2004 amounted to 0.37. This is below the normative value (0.5) at which the borrowed capital can be compensated by the property of the enterprise. The indicator "Coefficient of autonomy" for the period from 2004 to 2005 decreased by -0.08 and in 2005 amounted to 0.30. It is also below the normative value (0.5) at which borrowed capital can be compensated by the property of the enterprise.


The indicator "Coefficient of the ratio of borrowed and own funds" (financial leverage), for the period from 2003 to 2004 increased by 0.39 and in 2004 amounted to 1.67. 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 company's dependence on borrowed funds. The permissible level is often determined by the operating conditions of each enterprise, primarily by the speed of turnover of working capital. Therefore, it is additionally necessary to determine the turnover rate of inventories and receivables for the analyzed period. If receivables turn around faster than working capital, which means a fairly high intensity of receipts at the enterprise Money, i.e. The end result is an increase in equity. Therefore, with a high turnover of material working capital and an even higher turnover of receivables, the ratio of own and borrowed funds can be much higher than 1.


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


Indicator "Coefficient of maneuverability", 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 coefficient of maneuverability characterizes what share of sources of own funds is in a mobile form. The normative value of the indicator depends on the nature of the enterprise's activity: in capital-intensive industries, its normal level should be lower than in material-intensive ones. At the end of the analyzed period CJSC "Kraitekhsnab" has a light structure of assets. 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 production.


Indicator "Coefficient of provision of reserves 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 below the normative value (0.6 - 0.8), as in 2003, 2004 and 2005. The enterprise lacks its own funds for the formation of reserves and costs, which was also shown by the analysis of financial stability indicators in absolute terms.


BIBLIOGRAPHY

1. The procedure for monitoring the financial condition of organizations and accounting for their solvency. Federal Service of Russia for Insolvency and Financial Recovery: Order No. 13-r of 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.
   Evaluation of the economic performance of a trading enterprise ON THE EXAMPLE OF THE MAIN PERFORMANCE INDICATORS OF THE ENTERPRISE SHOW THE USE OF 6 PRIVATE METHODS AND RECEPTIONS OF ECONOMIC ANALYSIS Financial condition of a trade organization and assessment of economic indicators

   2013-11-12

All business processes of enterprises are interconnected and interdependent. Some of them are directly related to each other, some are manifested indirectly. Thus, an important issue in economic analysis is the assessment of the influence of a factor on a particular economic indicator, and for this, factor analysis is used.

Factor analysis of the enterprise. Definition. Goals. Kinds

Factor analysis refers to scientific literature to the multidimensional section statistical analysis, where the observed variables are estimated using covariance or correlation matrices.

Factor analysis was first used in psychometrics and is currently used in almost all sciences, from psychology to neurophysiology and political science. The basic concepts of factor analysis were defined by the English psychologist Galton and then developed by Spearman, Thurstone, and Cattell.

Can be distinguished 2 goals of factor analysis:
- determination of the relationship between variables (classification).
— reduction of the number of variables (clustering).

Factor analysis of the enterprise- a comprehensive methodology for systematic study and assessment of the impact of factors on the value of the effective indicator.

The following can be distinguished types of factor analysis:

1. Functional, where the effective indicator is defined as a product or an algebraic sum of factors.
2. Correlation (stochastic) - the relationship between the performance indicator and factors is probabilistic.
3. Direct / Reverse - from general to specific and vice versa.
4. Single stage / multi stage.
5. Retrospective / prospective.

Let's take a closer look at the first two.

In order to be able to factor analysis is necessary:
All factors must be quantitative.
- The number of factors is 2 times more than the performance indicators.
— Homogeneous sample.
— Normal distribution of factors.

Factor analysis carried out in several stages:
Stage 1. Selected factors.
Stage 2. Factors are classified and systematized.
Stage 3. The relationship between the performance indicator and factors is modeled.
Stage 4. Evaluation of the influence of each factor on the performance indicator.
Stage 5 Practical use of the model.

Methods of deterministic factor analysis and methods of stochastic factor analysis are singled out.

Deterministic factor analysis- a study in which factors affect the performance indicator functionally. Methods of deterministic factor analysis - the method of absolute differences, the method of logarithm, the method of relative differences. This type of analysis is the most common due to its ease of use and allows you to understand the factors that need to be changed to increase / decrease the effective indicator.

Stochastic factor analysis- a study in which factors affect the performance indicator probabilistically, i.e. when a factor changes, there may be several values ​​(or a range) of the resulting indicator. Methods of stochastic factor analysis - game theory, mathematical programming, multiple correlation analysis, matrix models.

Perform a factorial analysis of the phenomenon according to the multiplication model using the method of relative differences, absolute differences, the method of chain substitutions and formalization of the irreducible remainder and the logarithmic method.

a) absolute change: b) relative change:

Calculations

3,62*5,02*2,92*5,82=308,829

76,7807

=0,00

Examination

У4.52*5.02*4.02*5.72=521.7521

3,62*5,02*2,92*5,82=308,829

521,721-308,829=212,92

CONCLUSION: factor analysis calculations show that under the influence of all independent factors A, B, C, D, the effective factor Y increased by 212.92 units. Wherein Negative influence the productive factor Y was also affected by factors like B and D. Of these greatest influence factor D had, and its change caused a decrease in the effective factor Y by 9.12 units. At the same time, factors A and C had a positive impact on factor Y, of which factor C had the greatest influence, its change caused an increase in the effective factor Y by 145.264 units.

2) the method of "indecomposable remainder"

Isolated influence of factors

For factor A \u003d 0.9 * 5.02 * 2.92 * 5.82 \u003d 76.7807

B \u003d 0.00 * 3.62 * 2.92 * 5.82 \u003d 0.00

C \u003d 1.1 * 3.62 * 5.02 * 5.82 \u003d 116.3397

D \u003d -0.10 * 3.62 * 5.02 * 5.82 \u003d -10.5763

"Indecomposable residue" is determined by the formula

NO \u003d No \u003d 212.92-182.5441 \u003d 30.38

CONCLUSION: factor analysis calculations show that under the influence of all independent factors A, B, C, D, the effective factor Y increased by 182.5441 units. At the same time, factors such as B and D also had a negative impact on the effective factor Y. Of these, factor D had the greatest influence, and its change caused a decrease in the effective factor Y by 10.5763 units. At the same time, factors A and C had a positive impact on factor Y, of which factor C had the greatest influence, its change caused an increase in the effective factor Y by 116.3397 units. The error was 30.38.

3) Logarithmic method.

			Absolute off	Individual index i

I Lg (i) i /Lg (i) y

For factor A = 0.09643*212.92/0.22775=90.151

For factor B = 0.00*212.92/0.22775=0.00

For factor С = 0.13884*212.92/0.22775=129.8

For factor D = -0.00753*212.92/0.22775=-7.0397

90,151+0,00+129,8+(-7,0397)= 212,9113

CONCLUSION: factor analysis calculations show that under the influence of all independent factors A, B, C, D, the effective factor U increased by 212.9113 units (the error in the calculations is associated with rounding off the change in the factor) At the same time, factor D had a negative impact on the effective factor Y , and its change caused a decrease in the effective factor Y by 7.03997 units. At the same time, factors A and C had a positive impact on factor Y, of which factor C had the greatest influence, its change caused an increase in the effective factor Y by 129.8 units.

4) The method of absolute differences. Y= A*B*S*D

b) general change in the results of factors

Decision

0,9*5,02*2,92*5,82=76,781

4,52*0,00*2,92*5,82=0,00

4,52*5,02*1,1*5,82=145,2639

4,52*5,02*4,02*(-0,1)= -9,1215

76,781+0,00+145,2639+(-9,1215)= 212,923

Checking the results:

У4.52*5.02*4.02*5.72=521.7521

3,62*5,02*2,92*5,82=308,829

521,721-308,829=212,92

CONCLUSION: factor analysis calculations show that under the influence of all independent factors A, B, C, D, the effective factor Y increased by 212.923 units. At the same time, factor D had a negative impact on the effective factor Y, and its change caused a decrease in the effective factor Y by 9.12 units. At the same time, factors A and C had a positive effect on factor Y, of which factor C had the greatest influence, its change caused an increase in the effective factor Y by 145.2639 units.

5) the method of chain substitutions.

	Result
At

are called factor analysis. The main varieties 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 generalizing economic indicator is functional. The latter means that the generalizing indicator is either a product, or 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 generalizing economic indicator is probabilistic, otherwise - correlational.

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, the change in the argument can be combined with several values ​​of the change in the function.

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

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

Classification of factors affecting the effectiveness of the organization

The factors whose influence is studied during the conduct are classified according to various criteria. 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 main and secondary. The main ones include factors related to the use and materials, as well as factors due to the supply and marketing activities and some other aspects of the functioning of the organization. The main factors have a fundamental impact on the general economic indicators. External factors that do not depend on this organization are due to natural and climatic (geographical), socio-economic, as well as external economic conditions.

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

Factors can be divided into extensive (quantitative) and intensive (qualitative) on the basis of 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 the change in the number of workers will be an extensive factor, and the change in the labor productivity of one worker will be an intensive factor.

Factors affecting economic performance, according to the degree of their dependence on the will and consciousness of employees of the organization and other persons, can be divided into objective and subjective factors. Objective factors may include weather conditions, natural disasters that are independent of human activity. Subjective factors are entirely dependent on people. The vast majority of factors should be classified as subjective.

Factors can also be subdivided, depending on the scope of their action, into factors of unlimited and factors of limited action. The first type of factors operates everywhere, in any branches of the national economy. The second type of factors affects only within an industry or even an individual organization.

According to their structure, the factors are divided into simple and complex. The vast majority of factors are complex, including several constituent parts. However, there are also factors that cannot be divided. For example, capital productivity can serve as an example of a complex factor. The number of days the equipment has worked in a given period is a simple factor.

By the nature of the impact on generalizing economic indicators, there are direct and indirect factors. Thus, the change in products sold, although it has an inverse effect on the amount of profit, should be considered direct factors, that is, a factor of the first order. The change in magnitude material costs has an indirect effect on profit, i.e. affects profit not directly, but through the cost, which is a factor of the first order. 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, there are measurable and non-measurable factors.

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

Factor economic analysis

In those signs that characterize the cause, are called factorial, independent. The same signs that characterize the consequence are usually called resultant, dependent.

The combination of factor and resultant signs that are in the same causal relationship is called factor system. There is also the concept of a factor system model. It characterizes the relationship between the resultant feature, denoted as y, and factor features, denoted as . In other words, the factor system model expresses the relationship between general economic indicators and individual factors that affect this indicator. At the same time, other economic indicators act as factors, which are the reasons for the change in the generalizing indicator.

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

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

Two types of relationships between generalizing indicators and factors influencing them are studied:

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

functional connection- this is such a relationship in which each value of the factor (factorial attribute) corresponds to a well-defined non-random value of the generalizing indicator (effective attribute).

Stochastic connection- this is such a relationship in which each value of a factor (factorial attribute) corresponds to a set of values ​​\u200b\u200bof a generalizing indicator (effective attribute). Under these conditions, for each value of the factor x, the values ​​of the generalizing indicator y form a conditional statistical distribution. As a result, a change in the value of the factor x only on average causes a change in the general indicator y.

In accordance with the two considered types of relationships, there are 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 the results of the analysis is ensured by the use of economic and mathematical methods of research.

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 the change 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.