CC BY
11Journal of Siberian Federal University. Humanities & Social Sciences 4 (2013 6) 562-573
УДК 332.012.2
The Elasticity Estimation of the Business Value as a Tool of Factors Analysis of the Enterprises Development (on Example of Achinsk Alumina Combine)
Valentina F. Lapo* and Michael V. Kravchenko
Siberian Federal University 79 Svobodny, Krasnoyarsk, 660041 Russia
Received 27.06.2012, received in revised form 15.11.2012, accepted 10.03.2013
The business value models have found a wide application in the modern management of organization. They also can be applied to analyzing the technological efficiency based on the value elasticity coefficients. Some Russian alumina enterprises have obvious problems with further raw materials providing. This problem has technological and economic aspects. The enterprises such as Achinsk alumina combine are trying to solve a problem of involving worse quality raw materials into processing. In this paper the authors have attempted to adapt the Gordon's value model to the technological factor analysis. It allows taking into consideration the significant features of complex processing; and determining the possible consequences of the deterioration of key technological indicators. So, the authors emphasize the need of developing the economic instruments of estimating the multi-nomenclature technologies.
Keywords: business value, Gordon's model, elasticity coefficients, complex raw materials, Achinsk alumina combine
Introduction
The business value estimation methods have found wide application in modern management of organization. There are different approaches considering separate aspects of the value basis managing. It is necessary to note that each of the existing approaches is not independent. It is possible to offer the following classification of approaches to management on the basis of business value estimation:
- approaches which consider modelling of business value as a tool to analyze the enterprise development factors. I.Egerev
© Siberian Federal University. All rights reserved
* Corresponding author E-mail address: [email protected]
and S.Mordashov's approaches are to be mentioned among this group; approaches which consider a problem of stability and balanced growth of company value. The studies of K.Uolsh and A.Damodaran form this group; approaches considering an estimation problem of a business evolution scenario. T.Kouplend, T.Koller, J.Murrin's works, along with the works of R.Brejli, S.Myers form this group;
approaches, which are based on financial and economic analysis of the company.
According to this approach the company value increase is connected with improvement of financial and industrial parameters in the first place. There are, for example, the M.Bertonesh, R.Knight and Y.Kozyr's researches in this group. All the approaches in the aggregate make the more or less complete business management system which is focused on the value growth.
T.Kouplend, T.Koller and J.Murrin were one of the first to offer the business value estimation as a complex of the efficiency parameters of the company baseness value, and basic guideline in management [5]. The essence of the given approach is to define the gap between the company value in the share market and its internal value counted by an income flow capitalization. The company's management should develop the consecutive plan of internal and external improvements to reduce such gap. However, there are the specific tools of estimation and analysis of the company value presented in a less degree in approaches of those authors.
The profiTable approach advantages, founded by I.Egerev and S.Mordashov, are used to business valuation, on which basis the tools of analysis for purposes of managing are offered [9, 10]. The authors offered the mathematical model of company value and spent the factors elasticity analysis specifying separate parameters of Gordon's model. The calculation ofvalue elasticity coefficients for a company allows investigating a potential deviation of business value by changing one of parameters.
K.Uolsh and A.Damodaran consider a problem of balanced growth of the separate value model parameters. K.Uolsh approves that it is necessary to be guided by internal company potential, which is defined by the cumulative capital increase, under estimation of long-term growth rate of a monetary stream [1].
A.Damodaran has investigated the influence of financial leverage on value of the company taking into account the risk of bankruptcy connected with the size of duty covering factor [4]. The basic conclusion is the following: there is an optimum size of loan capital under which the capital value estimate is maximal.
The scenario concept of the company development estimation in management is developed by R.Brejli and S.Myers [3]. Within the framework of the concept at the first stage of estimation the manager defines a basic variant of company development and estimates the principal value. Further, the alternative company development variants or scenario are investigated, in which some model parameters are changed simultaneously. Thus, there is a potential value deviation from the basic level which is possible to estimate under different assumptions about the company development.
Other approaches are based on generalization of conclusions received by tools of financial and economic analysis of company's activity. In general such approaches contain the recommendations on the company work improvement, which have positive impact on the value [2, 6]. However this approaches does not reveal the connection between the offered recommendations and the basic value analysis tools.
Thus, the modern practices of the company value managing consist of the following techniques:
1. The company value modeling by detailed elaboration of the Gordon's model parameters.
2. The analysis of internal and external circumstances of the company.
3. Development of the variants or scenarios of the company development.
4. Estimating the company value according to the different variants of development.
5. Defining the key value factors by the elasticity parameters analysis, and analyses
of possible volatility of the separate model parameters.
6. Acceptance of administrative decisions being focused on increase of company value, and also on its stability to possible fluctuations of separate model parameters.
The basic accent in presented work is made on the business value factors analysis with using of the value elasticity coefficients to major factors of manufacture. The authors have attempted to adapt the elasticity analysis approach to investigate factors of value of enterprise processing complex raw materials.
The object of the research is Achinsk alumina combine (AGC) located in the Krasnoyarsk region and processing the nepheline ore to produce an alumina and other different products: soda ash, potassium sulfate, potash and cement. The supplier of the nepheline ore on the alumina combine is the Kiya-Shaltirsky deposit located in the Kemerovo area. The urgency of research is caused by a gradual exhaustion of stocks of Kiya-Shaltirsky deposit [12]. Ores of AGC's reserve deposits (Gorjachegorskoe, Tulujulskoe, Andrjushkina rechka, etc.) are characterized by the considerably worse chemical compound, which demand additional expenses for beneficiation of ore [11]. The problem of involving into processing less qualitative nepheline ores still remains unsolved for the Russian aluminum industry. Complex processing of natural resources will be preferable in long term, as stocks of high-quality raw material in the world are limited and tend to deplete.
Traditional techniques of estimation of the raw material processing technologies basically use the output parameters, cost prices, and poorly count market factors. The other existing techniques based on cost price analysis within the correlation and regression methods meet the certain technical estimating problems in view of the insignificant variation range of technological
parameters and also does not consider impact of market factors. To estimate the efficiency of the interconnected multinomenclature manufacture is demanded to develop the approach considering a number of other factors including risks. Using the enterprise value as the general efficiency indicator allows considering following significant factors:
1. Market prices for products and basic industrial resources.
2. Specific technological parameters.
3. A possible deviation between the realized product and manufactured product, which reflects influence of demand fluctuation.
4. The risks connected with structure of realization.
5. Demanded profitableness of the capital.
Key advantage of the enterprise value
estimation as the efficiency parameter is the opportunity to investigate the offered technological decisions to concrete conditions of enterprise functioning.
The purpose of this article is to define the key value factors by developing the value model and estimating value of the enterprise processing complex raw material and manufacturing a wide assortment of products. It supposed to study the business value sensitivity to technological and market factors.
Description of the baseness value estimation model
Under processing the Kiya-Shaltirsky nepheline ores the AGC produces the following basic products: alumina, soda ash, potassium sulfate, potash and cement. The generalized technological scheme of complex processing of the nepheline ores is shown on Fig. 1.
Let's note following features of considered technology:
1. Presence of the general complex industrial expenses connected with extraction, enrichment,
Mining the nepheline ore
Fuel oil
Mining the limestone
\_
Rush the ore
Ore sintering in the rotary kiln
Leaching the cake using the circulating fluid
Coal
Steam
Removing the saturated fluid
Removing the nepheline sludge
Precipitate the dissolved products
Cement production
Fig. 1. TFe complex technology of nepheline processing (Based on materials [7])
transportation and sintering of ore, which cannot be divided unequivocally between outputs of products. Complex expenses can have a significant share in the cost price for production. For example, the share of such oxpenses for Achinsk alumina combine may be abouC 60 percent.
2. Following feature is limitation of opportunities to change the products outputs nomenclature. The complex teuhnology of ore processing assumes boouecutive extractina of products under the scheme: nepheline sludge -alumina - soda ash - potassium sulfate - soda ash - potash. The soda ash is extracted in two steps.
3. The third feature of complex processing of the nepheline ores is the interconnected output. It means that the increase in the output of one product is probably only undet enpansion of production oC other products. Therefore, the possible problem of the complex enterprise may be the accumulation of non-realized products. The significant decrease in market demand on the same manufactured products of complex
enterprises can lead to significant decrease in revenoe position. Parameters of producfinn output on one ton of consumed working mixture (a crushed ore mix for sintering) are demonstrated in Table 1. The production output is a key techirological parameter on enterprise processing the complex row materials; it shows possible volume of each product manufactured on one unit of consnmed raw maoerial. The different variants of drawing up oo the ore mix apd the pred^h^n output corresponding to mix are shownm Table 1 for comparison: with nepheline and with a bauxites addition. The nepheline processing teehnelogy with the bauxites additive is studied by S.Vinogradov [8]; details on this scientific work are not the subject of our research. In this paper we consider the bauxite additive as the alteonative variant of nepheline ores prones«^. The main featuhe on this production variant is multidirectional economic effects: increasing the alumina output while the production of accompanying products (soda ash and potash) is reducing.
Table 1. Product's yield per ton of mix*
Yield Current production With bauxite addition
10 % 20 % 30 %
Alumina, kg/t 66,7 722 78 83,4
Soda ash, kg/t 37,1 24,5 133,7 5,2
Potash kg/t 1,2 0,8 0,44 0,17
Potassium sulfate, kg/t 2,2 2,2 2,2 2,2
* Calculated "with data from [Si]
4. The fourth feature of complex technology is ambiguity of an efficiency estimation of separate manufactures. In our opinion, using the business value estimation as the efficiency indieator allows to avoid problems with cost prices calculating. In case of complex processing there is no reliablecriterion off separating the general industrial expenses, therefoie the estimation of the coht peice foi manufactured output in many respects will depend on the selected method of distribution of technological and other general ewpenses. Ateo the business value is a preferable efficiency indicator for capital owners. The busineis value model allows analyzing the c apifal value incshmertt because of Ihe market changing (exteeeal parametess) and production structure (internal parameters).
In our paper we use the Gordon's capitalization model ¡as ihe fundamental instrument of the busmeso value esfimaeion. This model is ihowc in fosmula (1). The Gordon's model can be muclt closes to ohe market capital valfte psxrvided the invastors mire; mclined So make decisiions analyzing the possiblecash flows.
r — q
where PV is estimate of the present value of the own company's capital; CFx is the forecahting operating cash flow; q is the long-term growth rate of cash flow;
r is the required rate of return on the own capital.
We offer to uce the bu siness value models ae the insthsment of comparing the internal plans of company's development. Also these models are theoretically justified and allow avoiding the equivocation in ticeit ireatment. Below we aspdetailing the parameters o° cash flow (CF0) taking into consideration formulated features of complex processing.
The main distinction of complex processing is in the stcucture of cost-price. There are several groups of expenses:
1. Technological costs. This group includes expenses on extraction, enrichment, transportation, sintering the nepheline ores and obtaining the products. In complex processing the nepheline technological costs are connected with the production of the key product - alumina. So tine alumina production dttermines the; volume of consumed mixture lhat ir connected with specific technological parametees hnd market prices for corresponding induslefal eesources. Forimula (2) demonstrates the cumulative technological exp enses:
IC = Qal ■ SCb • (SCf-Pf+L + C + + SCe-Pe+SCh-Ph), (2)
where IC is general technological complex costs;
QaI is the expected realization volume of alumina;
SCb is specific consumption of mix per ton of alumina;
SCf is specific consumption of fuel per ton of mix;
SC,, is specific consumption of electricity per ton of mix;
SCh is specific consumption of heat energy per ton of mix;
L is specific costs of the ore transportation; C is specific costs of the ore concentration; Pf is the market price for fuel; Pe is the market price for electricity; Ph is the market price for heat energy. 2. Overhead costs. This group of expenses includes:
1) payment for labor and deductions to extra-budgetary funds;
2) repair and maintenance of the fixed assets;
3) amortization;
4) taxes including in the cost price;
5) costs of the nepheline sludge storing;
6) costs of storing the unrealized products;
7) heat energy and electricity costs on the production facility;
8) costs of supplying the production labour with the working clothes and special implements;
9) payment of rent;
10) other costs.
These expenses can be classified on variable and constant. In the business value model we assume that the variable expenses depend on the volume of production directly or indirectly. We assume that expenses for a payment change are proportional to the labour-output ratio and volume of production. Expenses for supplying the production labour with the working clothes and special implements vary directly to a number of the working personnel. Expenses for storage of non-realized production depend on a difference between volume of produced and realized
products, and also from specific expenses for warehousing a unit of products.
Other overhead costs have a conditional-constant character and do not depend on the volume of production. In our business value model we assume that these costs are not changing because the scale of production remains constant. Expenses for the nepheline sludge storage have the capital character connected with necessity of construction sludge storage in process of accumulation of waste. Formula (3) result definition of the overhead costs:
n
oc = YjVi-ii-Ps-0- + tf) +
i=i (3)
n
+ - Qi) -Ri + Rns+ A + VC + PC,
1=1
where OC is the total overhead costs;
V is the volume of production of the z-st product;
Q¡ is the volume of realization of the z-st przoduct;
l¡ is the labour-output ratio of the z-st p roduct;
Ps is the average annual wage of labour; tf is the rate of payments to the extra-budgetary funds;
R¡ is the specific costs on storing the z-st przoduct;
Rns is the specific costs on storing the nenspheline sludge;
A is the amortization of the capital assets; VC is the other total variable overhead costs;
PC is the other total constant overhead costs.
3. Management and commercial costs. Management costs have a constant component basically connected with a service of an administrative house; the variable part depends on a number of the administrative personnel,
which is connected with a quantity of workers of the basic manufacture. Commercial expenses are variable and de pend on the volume of shipped production.
¿t. Costs of the independent production. Some products require further processing within the framework of the independent production. For example, the nrpheline shidge are passing into the cement production, which supposes the second roasting the; sludge with edditional materials.
The structure of revenue doesn't need thee sepaeate classification. The revenue is the result oC multiplying the volume ee sold products on their market prices.
In our business value model we assume that the reserve of basic; technological materials is being paid by suppliers. So rhe difference between the cash flow and net profit is in the volume of the amortization. Thus, in formula 4 the detailed Gordon's business vslue model that can be used for estimating the technological efficiency of complex processing the nepheline ores is shown.
pv =
(Œ ?=i<?rPi -SU^-oç -/c -
r — q
(4)
- OC - MC - CC) ■ (1 - t„) + 4) ■ (1 + q)
r — q
where PV is the eseimaning current value of own capital of the complex production company; Pi is the market price for thr z-st product; DCt is the dicect costs on producing the z-st pro duct;
MC il the managing costs; CC is Che commercsal costs; tN is the income tax rate.
Estimation of value elasticity to facto rs
Formulated mathematical model allows providing a factor analysis using the impact quantities -fhe elasticity coefficients. This
approach gives the quantitative estimation of external and internal factors influencing on the business value for comparing development plans. The elasticity coefficients illustrate the possible increment of rhe efficiency indicator (the business value estimation) after changmg o ne of the model parameters (in y %.
Using the formula 5 the elasticity coefficients can be constructed.
_ SPV <P
10 _ "âif ' PV'
(5)
where yF is the elasticity coefficient of the business
value by the parameter F;
SPV
—— is the partial derivative of the business
S0 ^
value model.
Time derived elasticity coefficients formulas are demonstrated in Table 2. The alternative variant of calculating the elasticity coefficients is making the mafhematical model with using the tpecial computer programs (for example, MS Excel).
The mainproblem of the business value estimation is the absence of the correct information for calculating the cash flow. The annual financial report contains the information about the commercial result that differs considerably from the existing production result; in other words, the gap between production and financial cycles makes the barriers of using capitalization value models. Formulated formulas (1) - (4) make it possible to give the estimation of the normal cash flow matched with the expected producing volume. In Table 3 we give the estimation of the ACG cash flow for different psocessing variants listed in Table 1. In this paper we contider that it's correct to -view only the methodological aspect of the formulated AC G problem because the technological aspect is not investigated enough in the existing scientific literatu=e. Using the joint sintering processing with the bauxite addition as the alternative producing variant makes it easier to
- 5t8 -
Table 2. The elasticity coefficients of the busine as value*
Elasticity factors Formula
- selling price Pi-Qi-il- tN) YPi~ CF0
- volume of production (Pi - D( - /C* -VC*- CCt- MCd-Qi • (1 - t„) ^ _ CF0
- specific consumption ofmix IC • ( 1 - tN) Yscm CFj
- specific techno logicai indicators _ Q SCm -S Cj -Pr(l- tN) Ysc' SC0
- specific storage costs ZÎLjW- <?;)•/?r(l" tN) yRi sc0
- specific costs on building the sludge warehouse /^HM ■ ( 1 _ ttf) _ sc0
- laboriousness of production Sf=1 vt • k-ps • (1 + C0 • (l-Cv) Yli SS0
- increase rate of the cash flow SFo • (1 + r) (r - q)2
- required rate of return on the own capital CF0 -(1 + q) Yr (r - q)2
* Author's derivations
understand the mechanism of using the business value models in estimating the technological efficiency.
Using the formulas in Table 2 and company's economic indicators in Table 3 it's possible to calculate the elasticity coefficients asin the example given below:
Table 4 shows the resuhs of calculating the elasticity coefficients divided on two groups: technological and market. The market factors are external and they are forming the environment determining the technological efficiency. Managers have limited levers of the influence on the market environment.
Calculated elasticity coefficients allow providing the factor analysis of different production variants. The factor analysis gives the information about company's market
stability and key technological factors with their influence on the business value. The managers of AGC may use the vfewed approach for deteemining the permissible deviation of key technological factors within the fnamewo rk of the problem of choosing the optimal processing variant. Some conclusions of our paper are shown below:
1. Viewed production variants have the similar busine ss value but concentrating the production is increasing the impact of the alumina price as the key market factor.
2. The key technological factors are the next: the alumina yield, the specific blend consumption, the soda ash yield, the specific fuel and electrictty consumption. For example, increasing the specific blend consumption on iO % (as the result of decreasingthe raw materials equality) will kad
Table 3. Expected cash flows of ACG*
Indicators Current technology Variants of the bauxite addition
10 % 20 % 30 %
The volume of sales:
-alumina, ths tn. 1069,4 1155 1251,2 1336,8
-soda ash, ths tn. 595,1 392,8 220,2 83,3
-potassium sulfate, ths tn. 35,3 35,3 35,3 35,3
-potash, ths tn. 19,2 12,7 7,1 2,7
-cement, ths tn. 1400 1400 1400 1400
The revenue, m. rubles 24222 23685 23547 23565
-alumina, ths tn. 14700 15876 17199 18375
-soda ash, ths tn. 4941 3261 1828 692
-potassium sulfate, ths tn. 565 565 565 565
-potash, ths tn. 96 64 36 13
-cement, ths tn. 3920 3920 3920 3920
Cumulative costs, m. rubles 17120 16915 16778 16685
-technological costs, m. rubles 11451 11311 11218 11154
-overhead costs, m. rubles 4479 4414 4370 4341
-independent costs, m. rubles 1190 1190 1190 1190
Commercial costs, m. rubles 1211 1184 1177 1178
Management costs, m. rubles 1410 1334 1284 1250
Profit on sales, m. rubles 4480 4251 4307 4451
Tax on profit, m. rubles 896 850 861 890
Net profit, m. rubles 3584 3401 3446 3561
Amortization, m. rubles 950 950 950 950
Cash flow, m. rubles 4534 4351 4396 4511
Variation of the business -4,04 -3,05 -0,52
value, %
* Author's derivations with using materials [12, 13]
to losing the business value (as the cumulative production efficiency) more than 20 %.
3. Increasing the level of the bauxite addition leads to concentrated production of the alumina. In comparison with the current technology these production variants have the similar influence of varying the specific consumption of technological resources; but the development of accompanying products is losing the previous power.
4. To the side of market prices AGC has some safety margin. For example, increasing the
price for coal on 10 % leads to losing the business value no more than 4 %. But such deviation on the alumina market can be dangerous for the AGC financial stability.
5. In our opinion, the remainder of the unrealized products doesn't lead to huge losing the business efficiency even if decreasing the market demand is about 30 %. In this way, the business value is decreasing only by 10 %.
In conclusion it is necessary to note that business value models discover their application
Table 4. The elasticity coefficients*
Elasticity coefficients Current production With bauxite additive
10 % 20 % 30 %
Technological factors
-specific consumption of the fuel oil -0,48 -0,5 -0,49 -0,48
-specific consumption of the coal -0,36 -0,38 -0,37 -0,36
-specific consumption of the electricity -0,13 -0,12 -0,12 -0,11
-specific consumption of the heat -0,22 -0,21 -0,2 -0,18
-yield of the alumina 2,13 2,29 2,45 2,56
-yield of the soda ash 0,64 0,41 0,22 0,08
-yield of the potassium sulfate 0,08 0,08 0,08 0,08
-yield of the potash 0,01 0,01 0,003 0,001
-laboriousness of processing the fluid -0,35 -0,34 -0,31 -0,3
-laboriousness of processing the nepheline sludge -0,12 -0,12 -0,12 -0,12
-specific consumption of the blend -2,02 -2,08 -2,04 -1,98
-output of the cement production 0,17 0,34 0,34 0,33
Market factors
-price for alumina 2,6 2,77 2,97 3,1
-price for the soda ash 0,83 0,57 0,32 0,12
-price for the potassium sulfate 0,09 0,1 0,1 0,1
-price for potash 0,02 0,01 0,01 0,002
-price for cement 0,66 0,68 0,68 0,66
-volume of sales of the alumina 2,55 2,88 3,09 3,22
-volume of sales of the soda ash 0,88 0,61 0,34 0,12
-volume of sales of the potassium sulfate 0,1 0,1 0,1 0,1
-volume of sales of the potash 0,02 0,01 0,01 0,003
-volume of sales of the cement 0,78 0,81 0,81 0,79
-distance of the transportation -0,73 -0,76 -0,75 -0,73
-price for the fuel oil -0,48 -0,5 -0,49 -0,48
-price for coal -0,36 -0,38 -0,37 -0,36
-cost of ore mining and processing -0,11 -0,11 -0,11 -0,11
-cost of the electricity -0,39 -0,4 -0,39 -0,37
-wage -0,22 -0,21 -0,2 -0,19
-remainder of the unrealized products -0,27 -0,28 -0,27 -0,25
* Author's calculations
not only in the financial relations on share markets; they can be used also in decision making within the internal environment of the company, such as estimating the technological efficiency and choosing the plan of further development. The business value is a good cumulative indicator of the company efficiency; each business model is theoretically justified and assumes the balanced
set of external and internal factors. In our opinion, the AGC raw materials providing problem requires developing the adapted estimating approaches to the features of complex processing. The provided calculations show the opportunity to apply the elasticity coefficients to determining the permissible limits of the specific technological indicators deviation.
References
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Оценка эластичности стоимости бизнеса как инструмент анализа факторов развития предприятия (на примере Ачинского глиноземного комбината)
В.Ф. Лапо, М.В. Кравченко
Сибирский федеральный университет Россия 660041, Красноярск, Свободный, 79
Методы оценки стоимости бизнеса нашли широкое применение в современном менеджменте организаций. Основной акцент в представленной статье сделан на анализе факторов стоимости бизнеса с использованием коэффициентов эластичности стоимости. Авторы попытались адаптировать подход анализа эластичности к исследованию факторов стоимости предприятия, занимающегося переработкой комплексного сырья. Модель стоимости бизнеса адаптирована к производству, основанному на комплексных технологиях переработки нефелиновой руды. Были выведены и оценены технологические и рыночные коэффициенты эластичности стоимости для Ачинского глиноземного комбината.
Ключевые слова: оценка стоимости бизнеса, модель Гордона, коэффициенты эластичности, комплексное сырьё, Ачинский глинозёмный комбинат.
