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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.19 No.1 pp.78-92
DOI : https://doi.org/10.7232/iems.2020.19.1.078

# Prospects for the Development of Business Processes in Cooperation in the Economic Sphere of Energy Security (on the example of the Republic of Kazakhstan and France)

Saltanat T. Tayshanova*, Bibikhadisha Zh. Abzhapparova, Amirzhan K. Alpeissov, Rauilya T. Aitbayeva, Kurmangali G. Darkenov
Department of Regional Studies, L.N. Gumilyov Eurasian National University, Nur-Sultan, Republic of Kazakhstan
Department of International Relations, L.N. Gumilyov Eurasian National University, Nur-Sultan, Republic of Kazakhstan
Department of Regional Studies, L.N. Gumilyov Eurasian National University, Nur-Sultan, Republic of Kazakhstan
*Corresponding Author, E-mail: tashanova@kpi.com.de
January 2, 2020 January 17, 2020 February 1, 2020

## ABSTRACT

The interaction between the Republic of Kazakhstan and France is largely concentrated in the field of energy projects and building a strategy to ensure energy security. For the energy sector of Kazakhstan, the possibility of maintaining the export of products and resources to Western Europe is also determined by obtaining additional diversification in world markets. This contributes to the strengthening of sovereignty and the greater socio-economic stability of the country. The novelty of the research lies in the proposal of a model which would contribute to the formation of a positive balance of payments for exporting enterprises. The authors of the article have developed a model that meets the requirements of economic security for an enterprise, a significant share of whose products is sold on the foreign market and is competitive. The article notes that such a solution can be implemented with the participation of the enterprise in the world demand and the formation of permanent revenues to the budget in this way. The authors believe that the developed model should be applied mainly to strategically important exporting enterprises. The authors proposed to fully optimise the functioning of the enterprises related to the export of energy complex products.

## 1. INTRODUCTION

For a while, after gaining the independence, many people doubted that young States of Central Asia would stand the test. But the peoples of these countries, which have centuries-old historical roots, showed endur-ance and pragmatism in finding a way out of problematic situations, manage to adapt to new conditions. After the collapse of the Soviet Union, France began to pay great attention to Central Asia, countries that are at the center of geopolitical interests and occupy a key position in the subregion and have a huge energy potential (Gonnova and Kavtaradze, 2010). The leading country in Central Asia is Kazakhstan. During the years of independence, the Republic of Kazakhstan has achieved great success in the development of the economy and political sphere, and France considers Kazakhstan as a country with a great future. Strong development, economic growth, development of the energy sector, democratic mechanisms – all this creates a great image of Kazakhstan abroad (Johannsen and Leist, 2012a). As noted by experts, Kazakhstan has become a leader in Central Asia in terms of attracted investment, the figure amounted to more than 224 billion dollars. This was contributed to by a number of measures taken on behalf of the Head of state, President of Kazakhstan N.A. Nazarbayev.

Nowaday, among the Community of Independent States (CIS), Kazakhstan is the second on the list of partners of France, second only to the Russian Federation. Oil, ores, raw materials for the chemical industry and leather raw materials are supplied from Kazakhstan to France. Imports are medicines, food, perfumes, spare parts for certain types of equipment, cars, consumer electronics. It should be noted that Kazakhstan in its foreign policy priorities proceeds from the concept of multi-vector, when no preference is given to any one country. It can be argued that the country tries to adhere to a multi-vector policy in the field of energy. In contrast to Iran burdened with various kinds of embargoes and sanctions in the fuel and energy sector, over the years of independence, Kazakhstan has managed to implement the whole series of economic and social reforms (Scheuerlein et al., 2012) which opened the access for Foreign Direct Investment (FDI) to most international players. Countries such as China, Japan, Russia, France, the United Kingdom and the United States of America were able to freely enter the domestic market of Kazakhstan due to the favourable investment climate. The country has passed the stage of a certain economic transformation, assimilated the laws of the capitalist market and reoriented itself to the international market with all the following rules and conditions: the development of competitiveness, regular injections of FDI, organising the tenders, etc.

In particular, for such countries as Russia and China, it is one of the main determining factors. It is no exaggeration to note that one of the main engines of economic growth in the country was FDI in the oil and gas sector (Roelens et al., 2019). In the first decade of its independence, the country received more than $13 billion in foreign direct investment. Kazakhstan, to the extent possible, tries to use the revenues from the sale of fuel and energy complex most effectively by investing in infrastructure, transfer of advanced technology, development of the social sphere, etc. In the 2000s, Kazakhstan’s energy policy underwent a major transformation. Kazakhstan tried to bargain for greater control over its resources, oil and gas industry and export routes. It is no wonder that some of the innovations in this area, as well as the reforms have somewhat alienated Western countries, having limited the activities of international corporations in the country. However, such measures, on the contrary, contributed to greater penetration of China into the Kazakh market. Since 1991 before the imposition of international sanctions, Kazakhstan has also interacted with Iran, sending its oil from Aktau to the oil terminals of the City of Neka, located in the North of Iran. However, despite the economic crisis and the devaluation of the national currency, the Government of Kazakhstan froze electricity prices for the population till 2018. The equipment of energy facilities and infrastructure itself is aging every year, and in order to preserve the existing potential, the country is annually to invest millions of dollars. President of the Republic of Kazakhstan Nursultan Nazarbayev, when speaking at the 62nd session of the General Assembly of the United Nations in 2007, made a statement on the need to adopt the Eurasian Pact on the Stability of Energy Supplies, as well as to develop a Global Energy and Environmental Strategy within the United Nations. In addition, Kazakhstan put forward the idea of so-called Asian Energy Strategy. It is based on the idea of creating a reliable energy supply to the region, as well as optimal conditions ensuring equal benefits for the supply of energy resources to domestic and foreign markets, taking into account the energy policy, energy and environmental security of the countries of the region. In this regard, a model of econometric content, which is able to fully determine the possibility of structural development and functioning for ensuring sustainable economic results is considered. ## 2. MATERIALS AND METHODS Since the mid-XXth century the viability of an economic object has most often considered as the main integrated indicator of its efficiency (Atanelishvili and Silagadze, 2018;Silagadze, 2019;Awadid and Nurcan, 2019). At the same time, there is neither a generally ac-cepted decomposition of the efficiency analysis procedure by directions nor a single system of indicators covering these directions. P. Drucker from the point of view of viability of the enterprise pointed out 8 directions of the efficiency analysis (Drucker, 2006). In Ansoff’s research paper, the highest priority is return on capital investment (Ansoff, 1999). Johannsen and Leist proposed three directions (financial, operational and corporate efficiency), each of which is decomposed into lower-level directions (Johannsen and Leist, 2012b). According to the balanced scorecard conception, directions such as finance, customers, processes, growth and training are established (Hassen et al., 2019). According to the results of control of key indicators and factors of business processes and evaluation of overall efficiency based on situational approach, the procedure of interpretation of the analytical results is applied within the framework of goal setting (Cheikhrouhou et al., 2015). The essence of this procedure is to determine the necessary limits of indicators to prevent deterioration of the economic object’s efficiency (Haddar et al., 2014). Measurement of business process indicators at the enterprise or organization and in interfirm networks, data collection on problematic situations and analysis of cause-and-effect relationships between key indicators are the main stages in the management cycles presented in techniques such as DMAIC (Define, Measure, Analyze, Improve and Control), DMADV (Design, Measure, Analyze, Design, and Validate) and DMEDI (Define, Measure, Explore, Develop and Implement) relating to SixSigma Conception (Irani et al., 2001). Due to uncertainty of conditions and ambiguity of interpretation of results of the analysis of financial and economic activity it is difficult to establish exact value of input variables and compare to them the values of output variables. Therefore, managers tend to give these results a qualitative evaluation with the help of statements in natural language, that is, to formulate linguistic variables. ## 3. RESULTS AND DISCUSSION ### 3.1 Research on the Development of Cooperation Between Kazakhstan and France in the Energy Sector The cooperation between Kazakhstan and France in the energy sector has developed and is developing both in a bilateral format and in the framework of Kazakhstan’s participation in multilateral projects in France. Within the framework of TACIS, two so-called interstate programs have been created: Transport Corridor Europe-the Caucasus-Asia (TRACECA) and Interstate Oiland Gas Transportation to Europe (INOGATE). Through these programs, France supports the creation of transport infrastructure. France needed Kazakhstan’s support for the TRACECA project. The TRACECA project was first considered at a Brussels conference in May 1993. Following the conference, the European Union made a decision to develop a transport corridor in the West-East direction from Europe, crossing the Black Sea, through the Caucasus and the Caspian Sea with access to Central Asia. The TRACECA project is important for increasing the export of Kazakhstan’s oil and gas resources to the European market. The development of these transport corridors is of particular relevance in connection with the future growth of oil production in the Caspian region and the reconstruction of the sea trading port of Aktau. To date, 39 studies of technical assistance in the amount of 57.405 million euros and 14 investment projects for rehabilitation of infrastructure in the amount of about 52.300 million euros have been funded under the TRACECA program. However, it is necessary to note a number of shortcomings associated with the implementation of the TRACECA program, both from the European Union, and from the government of the participating countries, local specialists directly working on projects. It is rather difficult to monitor the expenditure of financial investments in the project, given the high level of corruption of officials, it can be assumed that the funds allocated through the TRACECA program do not always go for their intended purpose. At the same time, there is no clear coordination between the governments of the Central Asian participating countries on the implementation of the TRACECA program. There is some competition between states on the implementation of projects in order to attract large financial resources to their state. Kazakhstan is also a member of the international cooperation program in the field of energy between the European Union, the Black Sea and Caspian states of INOGATE since its inception in 1996. For the first time, the INOGATE program (Eng. INOGATE – Interstate Oiland Gas Transportation to Europe) appeared in 1995 as a mechanism for interstate transportation of oil and gas to Europe. Initially, this applied only to oil and gas pipelines from Eastern Europe and the Caucasus to the European Union. In 2001, a Framework Agreement on cooperation in the development and modernisation of pipelines between the EU and 21 countries was signed in Kiev. This program is in line with the global strategy of the European Union regarding the countries of the Central Asian region. It should ensure the efficient export of energy resources through the Caspian and Black Seas to Europe. The European Union has proposed this program as a route, which should complement all traditional routes. To implement this Program at the interstate level, the Umbrella Agreement “On the Institutional Framework for the Establishment of Interstate Oil and Gas Transportation Systems” was adopted. France has significant interests, as a large potential consumer of energy resources, primarily oil and gas. In general, these interests boil down to France having a vote on issues related to energy production in the region, the creation of a network of oil and gas pipelines and the issue of jurisdiction of the Caspian Sea. Despite the fact that the legal status of the Caspian Sea has not yet determined, France shows a keen interest in this region. After September 11, 2001, the potential for a French contribution to ensuring regional security and greater involvement in regional politics appeared. It is clear to the European Commission that Caspian resources should play an important role in the energy supply of Europe in the future (and at the same time reduce the EU’s dependence on Russia). In 2006, Kazakhstan joined the French-supported Baku-Tbilisi-Ceyhan (BTC) oil pipeline. In October 2008, the first shipment of oil was sent from the Tengiz field. In 2009, the volume amounted to more than 1.9 million. However, in 2010, oil supplies through this pipeline were discontinued due to disagreements regarding transportation tariffs. However, Kazakhstan began pumping its oil through the BTC in October 2013. In addition, France seriously counted on Kazakhstan in terms of diversifying oil and gas transportation routes, as one of the participants in the Baku-Tbilisi-Ceyhan project. Along with integrated energy and climate policies in 2007, in order to strengthen energy and politi-cal cooperation with Central Asian countries, the European Union adopted the European Union and Central Asia: Strategy for a New Partnership for 2007-2013. This Strategy explicitly stated that the region represents strategic interests for the European Union in the field of security, stability and diversification of energy resources. Moreover, the strategy was “designed to bring together the problems of energy supply and security – the main areas of European Union interest in the region”. At the same time, exchange in the energy field, presumably experience, knowledge and technology, is one of the priority objectives of cooperation between the European Union and Central Asia. Within the framework of the Strategy, more than 750 million euros of total investment were allocated. Of these, 1.7 million euros were invested in a project called “Assistance in the field of energy and transport: diversification issues” in 2007 to assist the governments of Central Asia in developing coordinated national energy policies and updating regulatory frameworks for a long-term process of bringing them into line with international and European Union standards. It can be said that at the moment France prefers to work more in a bilateral format with major energy suppliers, including Kazakhstan. This is partially explained by the strategic importance of uninterrupted energy supplies from third countries and a certain share of France’s vulnerability to energy security. In industrial terms, the presence of France is determined by two strategic investment projects. The first is the investment of Areva, which is developing jointly with Kazatomprom uranium deposits, which makes Kazakhstan the largest global supplier of uranium. The second is Total’s investment in North Caspian Operating Company (NCOC), a consortium developing the Kashagan oil field. Hydrocarbons from this field will provide in the future 10% of oil consumption by the European Union. Thanks to the activities of Total and Areva companies, the main recipient of French investments has historically been the energy sector. Total has been in Kazakhstan since 1992 and is the holder of 16.8% in the consortium of the North Caspian Operating Company, the operator of the Kashagan oil field in the Caspian Sea. Areva has been operating in Kazakhstan since 1996 as part of the Katko a French- Kazakhstan Joint Venture enterprise, which was created jointly with Kazatomprom for uranium mining. Thanks to several projects in the field of solar energy, the field of renewable energy sources is also the sphere of application of French technologies in Kazakhstan. Trade and economic cooperation between France and Kazakhstan is characterised by its dynamism and complementarity. If earlier the main attention was traditionally paid to cooperation in the extractive sector, now, with the arrival of large groups of companies in the transport sector, as well as the implementation of the French-Kazakh partnership in many industrial sectors (auto industry, metallurgy, aeronautics, defence industry, pharmaceuticals, cement production, municipal services, renewable energy, agriculture), France diversifies its activities in Kazakhstan. In 2015, direct French investment in Kazakhstan is almost$11 billion, which puts it in third place among foreign investors after the Netherlands and the United States. As for the trade turnover, which is dominated by energy imports from Kazakhstan, in 2014, its volume amounted to 4.9 billion euros, against 6 billion euros in 2013. The 18.7% decrease is mainly due to the reduction in French energy costs due to lower oil prices. Nevertheless, France remains in 5th place (6%) among consumers of Kazakhstani exports, after Italy, China, the Netherlands and Russia. It should be noted that relations between Kazakhstan and France in the energy sector are developing both through multilateral and bilateral contacts. So, for example, the deal on the delivery of NAC Kazatomprom JSC to the French company ElectricitedeFrance (EDF) 4,500 tons of natural uranium concent rate for 2021-2025, EDF is Europe’s largest operator of nuclear power plants.

Kazakhstan is an important partner for France in connection with its balanced multi-vector foreign and energy policy, which has strengthened its role in the re-gion as a bridge between Europe and Asia. Kazakhstan is also a key player in the world export of uranium and many other important supplies of raw materials in France, which are necessary for the use of renewable energy sources. France imports from Kazakhstan about 5-6% of its total oil consumption and 21% of its uranium demand. Energy dialogue is one of the key components of Kazakhstan’s cooperation with France and is developing quite successfully. According to European experts, due to the increase in production and exports to France, “Kazakh-stan is contributing to the diversification of energy sources for the European Union, thereby strengthening the energy security of the European Union.” As the country ranks eleventh in the world in terms of global energy reserves, and by 2020, it is assumed that Kazakhstan will become the second largest oil supplier to world markets from non-Organization of the Petroleum Exporting Countries, any small energy or political fluctuations can seriously affect the regional situation.

For France, the overall regional, economic and strategic importance of Kazakhstan has grown beyond its geographic location and current oil exports. Kazakhstan’s Gross Domestic Product (GDP) continues to exceed GDP of the other four Central Asian states. The country’s business climate is the best in Central Asia, which positively affects the implementation of future energy projects. In particular, Kazakhstan plans to play an active role in new transcontinental transport routes, such as the Western Europe-Western China transport corridor, the EU Europe-Caucasus-Central Asia transport corridor (TRACECA), as well as China’s new “One Belt, One Road” concept. Over the past two decades, strong and mutually beneficial relations in the field of energy have formed between Kazakhstan and France. Large French energy companies have invested heavily in Kazakhstan’s oil and gas industry.

Most Kazakhstan experts are firmly convinced that France’s interests in the field of energy, both in re-gional and bilateral formats, are long-term and stable. The natural resources of Central Asia, access to them, as well as the diversification of their transportation routes, were a permanent priority in relations between France and the region. And they will continue to remain them, despite political and economic turbulence and other geopolitical changes. Thus, today France, influencing the development of a transport corridor along which oil and gas will be transported to Europe, can act as a kind of arbiter and guarantor of stability, both in the face of specific countries and in the person of the whole organisation. Kazakhstan intends to further develop mutually beneficial cooperation with France in various areas of the economy, such as energy, engineering, chemical, metallurgical and light industry, pharmaceuticals, agriculture, transit and transport complex, telecommunications. The participation of Total in the Kashagan field development project is the core direction of Kazakh-French cooperation in this area. This company was also selected as a strategic partner of National Company KazMunayGas on the Kurmangazy project. The company GazdeFrance is showing increased interest in cooperation in the gas industry, intending to invest \$ 1 billion in Kazakhstan. Kazakhstan is ready to develop cooperation on mutually acceptable terms with the Gas de France company on the Khvalynskoye project.

The best example of joint cooperation in the field of nuclear energy is the activity of the Katko a French- Kazakhstan Joint Venture, created by National Company KazAtomProm and Kozhema (Areva group), which is developing the Moyynkum uranium deposit in the Sozak region of the South Kazakhstan region. Next, let’s consider a model that can ensure the sustainability of the work of business structures that have been tested and presented in bilateral cooperation between Kazakhstan and France. First, a system of indicators is formed according to the organisational structure of the economic object and the main directions of the analysis of efficiency and planning of its activity (Awadid et al., 2019). For each indicator, ranges and intervals of values that correspond to subjective evaluations of their significance are empirically established (Pinggera et al., 2015). Net profit is one of the main indicators of the analysis of the economic object’s efficiency. It is also a major factor in its development through the use of undistributed profit. It is characterised by a zero point P0=0 (which can correspond to a break-even point) and a range with positive values that are broken down into a sequence of intervals of the same or different size:

$[ P 0 , P 1 + ] , P 1 + , P 2 + , ... , P J − 1 + , P J +$
(1)

The sequence of intervals of this range testifies to economic growth, accumulation of reserves, formation of financial and economic potentials for the development of the enterprise. At the same time, if the enterprise aims to maximise profit and profitability, it can lead to the decrease of the liquidity of the enterprise. The range of negative net profit values consists of intervals of loss indicator values:

$P 0 , P 1 − , P 1 − , P 2 − , ... , P J ˜ − 1 − , P J ˜ −$
(2)

The sequence of damage intervals is character-ised by the decrease of solvency and the increase of the probability of bankruptcy. Every m-th profit/loss interval

$P ^ m = { P m } = { [ P j ˜ − 1 − , P j ˜ − ] } j ˜ = 1 , j ¯ ∧ { [ P j − 1 + , P j + ] } j = 1 , J ¯$
(3)

has a qualitative evaluation that approximately reflects the efficiency of the enterprise. Its clarification occurs through the use of other interrelated financial indicators: profitability $( R )$, receivables $( A R )$ and payables $( B R )$ and liquidity. It is obvious that the dynamics of the financial results of the enterprise’s activity is affected by inflation, so it is necessary to recalculate the indicators in the prices of the previous period. Between the intervals of net profit values $( P ^ m )$ and profitability of the enterprise’s activity $( P ^ m )$ mutual correspondence is established, which allows to assert the identity of the ranks $γ m$ of these ranges:

$γ ( P ¯ m ) ≡ γ ( R ^ m ) = γ m$
(4)

$∏ m γ m = Γ$
(5)

Starting with a certain gradation $P j N R + ( j N R ∈ j )$ there is an undistributed profit NR which is aimed at achieving the goals in the development strategy of the economic object. $N R$ indicator is determined in the calculations of the stability coefficient of economic growth $( S E G )$ designed to evaluate the efficiency of the use of resources of the economic object and the dynamism of its development:

$S E G = N P O C$
(6)

where $O C$ is owned capital. Part of financial indicators $K l ˜ ( i ˜ ∈ I ˜ F i n ⊂ I F i n )$, as a rule, relative values has empirically established standards (intervals). For example, the recommended interval of absolute liquidity coefficient is 0.1-0.2. However, the same value of the indicator can be established for different impact of factors in different situations. Therefore, for intervals, m value of these indicators $K i ˜$ can be defined by $l m$ linguistic variable which characterises their significance for the economic object through the function of belonging of m-th interval to $l m$ characteristic:

$0 ≤ μ ( l m , K i ˜ , m ) ≤ 1 ∑ m μ ( l m , K i ˜ , m ) = 1 ∀ i ˜ ∈ I ˜ F i n$
(7)

The main financial indicators should also in-clude the share price coefficient, return on investment based on cash flow, coefficient of sales revenue to total capital, sales volume per employee, liabilities to owned capital and correlation of dividend payments to net profit. In the analogical way the indicators and the system of indicators in other directions of the analysis of the enterprise efficiency, the ranges of their values and releavant qualitative evaluations (in the form of linguistic variables) are determined. Efficiency indicators of the process of managing relations with consumers (“Customers” direction) are profit from the consumer (income for the period of cooperation with the consumer); number of customers, including the number of regular customers; sales revenue; sales volume; customer satisfaction degree; customer loyalty degree (Grolinger et al., 2014). To improve the adequacy of the evaluation of the financial efficiency of the enterprise, the combination of financial results is carried out. One of the ways of combined use of financial indicators is to build of regression models and discriminant functions (Koschmider et al., 2010). Another way to ensure the combined use and interpretation of the financial results of the enterprise’s activity is to determine the relationship between the membership functions $μ ( l m , K i , m )$ through the use of multidimensional membership functions which are represented as follows:

$μ q ( d ) = I ∨ i = 1 ( M ∧ m = 1 μ ( l m , K i , m ) )$
(8)

$q = { q 1 d , ... , q g d , ... , q G d }$
(9)

where equation (9) is fuzzy characteristics of the financial condition of the economic object. There occurs generalisation of the results of the analysis of the economic object in all directions $〈 D I M 〉$, interpretation of the situation as a whole $( S )$ and identification of the most significant factors. The general formulation of the problem of qualitative interpretation of situations in economic activity involves the formation of a knowledge base containing many records as follows:

$K 1 1 = b 1 1 ∈ m 1 , j 1 = ( b j 1 , 1 , b j + 1 1 , 1 ) ∧ ... ∧ K i d = b i d ∈ m i , j d = ( b j i , d , b j + 1 i . d ) ∧ ... , S = Q 1 ∨ ... ∨ Q g$
(10)

where $K i d$ is i-th indicator (in the d-th direction); $b i d$ is its numerical value; S is the situation in the eco-nomic object; $Q g$ is g-th evaluation of the situation. The analysis of efficiency of economic object’s activity uses subjective and objective evaluations of the situation change which are formally cause-and-effect relationships between the key indicators. They are complemented by events that, in turn, cause a chain of events with favourable and unfavourable consequences, which leads to benefits or undesirable costs (losses). The relationship between events and control parameters is determined by a set of rules, that is, based on the established values of input variables connected with a certain event, the values of output variables that are connected with the consequences and (or) management decisions are determined. Therefore, the situation analysis cycle includes procedures for determining association rules, identifying and evaluating risks. Intervals of indicators within one direction of efficiency of the economic object’s activity are united in two main intervals, the first of which signals threat, and the second one about possibility (competence). Subjective evaluations of the impact of control parameters $ν c$ on efficiency indicators $K i$ and, as a consequence, situation $S$, are established by processing optimistic, the most probable and pessimistic scenarios:

$K i ( v c ) = K i o p ( v c ) + 4 K i p r o b ( v c ) + K i p e s s ( v c ) 6$
(11)

where $K i o p , K i p r o b , K i p e s s$ are optimistic, the most probable and pessimistic scenarios according to i-th resulting value depending on the selected value of c-th control parameter. Management’s response to changes of the conditions and performance of the economic object causes the need for information on the possible intervals of changes of the resulting values (K1). The lower and upper boundaries of these intervals are calculated by formulas in which the fractional expression is the standard deviation:

$[ K ˜ i ( v c ) , K ˜ i ( v c ) ] = K i ( v c ) ± 2 K i o p ( v c ) − K i p e s s ( v c ) 6$
(12)

The set of ranges obtained $〈 K ˜ i , K ˜ 〉 i$ is pro-cessed to determine the total range $[ m ˜ i , m ˜ i ]$ for i-th indicator. For example, the minimum range is selected among $K ˜ i$ values and maximum one among those of $K ˜ i$ or average values are established. Thus, situational analysis methods, although they are not used to optimise business processes, are designed to determine the necessary boundaries of indicators in order to prevent situations that can worsen the economic object’s efficiency. Although specific criteria and efficiency indicators are used at different levels of the hierarchy, integrated criteria and indicators are calculated to evaluate the performance at the system-wide level. In the process of their formulation, they often refer to understanding of such characteristics as overall efficiency, overall quality, market status, customer loyalty, etc. (Deb et al., 2017). Integrated indicators are determined by generalising aggregated indicators, for example, reliability of business processes, quality and competitiveness of products, customer satisfaction, enterprise competitiveness, market (competitive) position and the like. As a rule, integrated efficiency indicators compare the performance with the costs for obtaining them, and the criteria are directed to the maximum positive result per unit of cost or minimum cost per unit of result (Johannsen and Fill, 2017). Aggregated indicators are synthesised by processing a set of partial indicators, which is decomposed into indicators of the 1st, 2nd and so on levels (Table 1).

The algorithm for integral evaluation of overall efficiency (or overall quality, market status or other integral characteristics) includes steps such as: overview of actual performance, data processing; studying the requirements of interested parties, expectations and feedback on actual state (results achieved); selecting key criteria and aggregated indicators for performance evaluation; selecting and calculating necessary indicators; assigning numbers to individual indicators $y i , j O C ( 2 )$ from the evaluation scale which is understood as the degree of the result achievement and the presence of the releavant property; determining the type of relationships between indicators by the degree of closeness of their impact on the overall state; determining the importance weights for every indicator; calculating the evaluations for aggregated $y i O C ( 1 )$ and integrated characteristics $y l O C ( 0 )$; obtaining evaluations for “target” and “ideal” states. For the latter one all $y i , j O C ( 2 )$ equal to the highest score (“4”); comparing the “current” evaluation with the “target” and “ideal” evaluations.

Depending on the method of processing expert judgments, the evaluation scale is approved. It is assumed that the higher the score, the better the value of the characteristic. The linguistic variables for the scores depend on the content and value of the preferred indicator. So, if it is considered that the indicator should correspond as precisely as possible to the target (desired or normative) value, then scale No. 1 is applied:

• 0 – not responding very much, very low, ab-sent;

• 1 – not responding, low, insufficient, rare, short;

• 2 – average;

• 3 – corresponds not fully, above average to large, sufficient, frequent, longstanding;

• 4 – fully, absolute, very frequent, perma-nent.

If it is desirable to have as greater value as pos-sible, then the variables of scale No. 2 can be:

• 0 – very low/small;

• 1 – low/small;

• 2 – average;

• 3 –high/big;

• 4 – very high/big.

In other case, when the lowest value of the indicator is predominant, scale No. 3 contains the following variables for scores:

• 0 – unacceptable, very big, maximum;

• 1 – big, longstanding;

• 2 – average;

• 3 – small, short;

• 4 – very small, minimum.

An integrated evaluation of performance (cur-rent state) for the established evaluation scales can be obtained using the method of logic of antonyms. For the indicators, which in the relationship have a weak impact on the higher level indicator, $H ( β )$ type, the additive convolution – decreasing in equations (13-14) is calculated. This means that if one of the indicators is assigned a small score, the indicator of the next level, dependent on it, can have a higher score on account of high scores by other indicators. With a close relationship, $H ( γ )$ type, it is chosen the way that with small evaluations of one of the indicators would reduce the contribution to the evaluation of the outcome indicator:

$y l O C ( 0 ) = ∑ i ψ i O C ( 1 ) y i O C ( 1 ) | i ∼ H ( β ) − log 2 [ 1 − ∐ i ( 1 − 2 − ψ i O C ( 1 ) y i O C ( 1 ) ) ] | i − H ( y )$
(13)

$y i O C ( 1 ) = ∑ j ψ i , j y i , j O C ( 2 ) | j ∼ H ( β ) − log 2 [ 1 − ∏ j ( 1 − 2 − ψ i , j y i , j O C ( 2 ) ) ] | j ∼ H ( γ ) ∀ i$
(14)

The evaluation obtained $y l O C ( 0 )$ is compared with target and maximum evaluations $y l o b j$ and $y l m a x$ which are obtained by substituting the necessary and maximum scores. When applying the problem and target method of analysis of business processes, based on the provisions of the situational approach, it should be borne in mind that the initial stage of building a tree of problems and a tree of goals is to respond to the identified deviations according to the indicators assigned to the hierarchical levels of management – system-wide, aggregated and local. Methods for determining deviations and procedures for their analysis should provide answers to the following questions: what the revealed deviations testify to; what they can lead to, and how they will affect the efficiency and performance of business processes, as well as the state of the economic object as a whole; if there are direct or indirect relationships between deviations at the same and different levels of the hierarchy; what countermeasures and preventive measures should be; when such measures should be taken and what they are aimed at. If there are no answers to the above questions, the goals will be more declarative, and the current decisions will be made by the departments autonomously and without reference to the whole tree of goals. Without the use of tools, which give a detailed view of the situation, and help set adequate goals, alignment of business processes will occur with delay and additional costs.

### 3.2 Analysis of Evaluation of Efficiency and Performance of Business Processes

Since the aim of management is not only a re-sponse to the recorded deviations but also to the causes of new ones, first of all, undesirable or unacceptable deviations, then the idea of balancing the goals of business process management is to use generalising evaluations of their efficiency and contribution to the achievement of a high level of organisational value (Bider and Perjons, 2015). Balance of goals is achieved through comprehensive researching production and flow processes and determining the possibilities of their adjustment from the position of scalability and resiliency to strengthen the market status, increasing the market value of the economic object and ensuring its financial stability. In evaluating the efficiency and performance of business processes, both indirect and direct indicators are used. The first of them characterises the financial side, and the second one does economic. PAF conceptual model (Prevention, Ap-praisal&Failure) also requires obligatory accounting of two types of expenses (Giaglis, 2001). The first type is the expenses for achieving the compliance with the previously stated parameters of business processes according to the requirements and expectations of interested parties, as well as quality standards. The second type is expenses and losses due to non-compliance with the changes that have occurred, and the identified deviations are often the causes of further events and deviations that entail additional expenses. If for any i-th indicator of the economic object’s activity there are such interested parties h и η, which have at the moment of t time different from one other activity $y i , t O C ( t )$ performance $( O C )$ evaluations by this indicator more than $Δ i , t O C ( l )$, then the procedure for the analysis of deviations and identification of Paper Money Guaranty (PMG) problems is applied:

$∀ i ∈ I ∃ ( h ∧ η ) | ∈ S H : | y i , t O C ( l ) ( h ) − y i , t O C ( l ) ( η ) | ≥ Δ i , t O C ( l ) ⇒ P M G$
(15)

Absolute and relative changes by business environment indicators are also included in the rules of causing the procedures with the determination of threats and possibilities (Simões et al., 2018). Planning of compensatory actions is initiated in case of exceeding the values of absolute and relative indicators of acceptable $Δ j , t ' B E$ values. Most often, based on the change during one period it is difficult to characterise its nature and significance for the economic object: if this change is a natural consequence of certain trends or an episodic event caused by unforeseen circumstances and if this change has a positive, neutral or negative impact on the state of the object. To give answers to these questions, one need to establish $τ ( i )$ length of time series for each selected business environment indicator and ways to obtain evaluative parameters and their gradations. For example, if for period of time $τ ( i )$ the average change of economic growth indicator is low than the minimum accepted one, it is necessary to find out what the reason was for this:

$∀ i ∃ τ ( i ) : 1 τ ( i ) ∑ t − τ ( i ) t y ˙ j , t B E ≤ Δ j , t ; B E ⇒ P V G$
(16)

It is necessary to compare the change evalua-tions in the business environment formed by the interested parties $〈 S H 〉$. If the expert group $〈 h S H 〉$ is supposed to gives changes of the j-th indicator of the business environment $( B E )$, numerical evaluation $z j , t B E$, then one of the conditions for causing the PMG procedure, for example, can be a check by the variation coefficient:

$∀ j ∈ J , h ∈ S H ∃ 1 z ¯ j , t B E ∑ h ( z j , t B E ( h ) − z ¯ j , t B E ) 2 ≥ Δ j , t B E ⇒ P M G$
(17)

The ideas of internal interested parties $( h 2 ∈ H 2 ) , ( h 1 ∈ H 1 )$ on expectations of external interested parties $H 1 ∩ H 2 ⊆ S H$ regarding each i-th characteristic of the final product and the results of business processes $y ˜ i , t O C ( l ) ( h )$. There is basically a close relationship between expectations and customer satisfaction, and customer loyalty to their supplier depends on satisfaction. The ability of a supplier to meet the expectations of consumers is regarded as a driving force in strengthening his market position. For a supplier to track customer expectations and measure customer satisfaction, continuous measurement and improvement of service quality and customer satis-faction evaluation techniques are needed. For a supplier to track customer expectations and measure customer satisfaction, continuous measurement and im-provement of service quality and customer satisfaction evaluation techniques are needed:

$∀ i ∈ I ∃ ( h 1 ∈ H 1 ∧ h 2 ∈ H 2 ) | H 1 ∩ H 2 ⊆ S N : | y ˜ i , t O C ( l ) ( h 1 ) − y ˜ i , t O C ( l ) ( h 2 ) ≥ Δ ˜ i , t O C ( l ) ⇒ P M G$
(18)

If the current quality of the final product and service of consumers, degree of social responsibility and environmental safety, and other characteristics of the values that external interested parties receive are lower than stated values τ periods ago, the tasks are set to prevent the decline of loyalty, trust and reputation:

$∀ i ∃ τ : y ˜ i , t − τ r l > y ˜ i , t r l ⇒ P M G$
(19)

Control over the implementation of measures to achieve the goals records the deviations between target and actual values by I indicators distributed by levels . If deviations revealed in one or more recent periods of time go beyond the acceptable limits, then a signal is received about the need to analyse the situation, check the adequacy of previously implemented actions and reconsider the goals in equations (20) or (21):

$∀ ä ∈ L , i ∈ I : ( x l , i , t e x − x l , i , t r l ) ≥ Δ ¯ l , i , t ( r l , e x ) ∨ ( x l , i , t r l − x l , i , t e x ) ≥ Δ ¯ l , i , t ( r l , e x ) ⇒ P M G$
(20)

$∀ l , i : { ( x l , i , t e x − x l , i , t r l ) ≥ Δ ¯ l , i , t ( r l , e x ) ∨ ( x l , i , t r l − x l , i , t e x ) ≥ Δ ¯ l , i , t ( r l , e x ) } ∧ { ( x l , i , t − 1 e x − x l , i , t − 1 r l ) ≥ Δ ¯ l , i , t − 1 ( r l , e x ) ∨ ( x l , i , t − 1 r l − x l , i , t − 1 e x ) ≥ Δ ¯ l , i , t − 1 ( r l , e x ) } P V G$
(21)

A conflict of goals between internal interested parties and partner organisations or within the project team slows or stops the changes required by an economic object. When revealing significant differences in goals, it is important to understand what each of parties is guided by: what needs, requirements and expectations. When evaluating the performance, technological development and market position, they are compared with the performance and state of similar economic objects, primarily among competitors. The clarification of the factors through which the lag occurs can start if for i-th resulting indicator, for which as greater as possible value is desirable, it is established that the coefficient of the eigenvalue to the value of the q-th analogue is less or equal to the lower boundary . The same happens when the coefficient of the values of the i-th indicator is considered, but for which as lower as possible value is desirable, equal or exceeds upper limit

$∀ i ∈ I 1 ⊂ I ∃ q : x i , t O C ( l ) x q , i , t O C [ l ] ≤ δ _ i , t O C ( l ) ∨ ∀ i ∈ I 2 ∈ I ∃ q : x i , t O C ( l ) x q , i , t O C ( l ) ≥ δ ¯ i , t O C ( l ) ⇒ P M G$
(22)

To compare the economic objects and determine possibilities of functioning and development of the investigated object, the data, which has been intentionally distorted by subjects of the business environment, can be used. Then when obtaining in the current t period updated values different from the previous ones, taken in (t −τ) period of time questions araise about their reliability and the expediency of reconsideration of the previously obtained conclusions:

$∀ i ∈ I ∃ q ∧ τ | ( t − τ ) ≺ t : ( x q , i , t − τ O C ( l ) x q , i , t − τ O C ( t ) ( t − τ ) − 1 ) ∉ [ φ _ q , i O C ( l ) , φ ¯ q , i O C ( l ) ] ⇒ P M G$
(23)

In goal setting and business process planning, constraints in the internal and external environment are taken into account. If these constraints provide opportunities for growth and improvement of financial, economic and market states, then the task is to find the most efficient ways to use these opportunities. Undesirable excess of the minimally necessary or required values over the possible (potential) ones in the current and next periods of time contributes to a detailed analysis of the situation:

$∀ l , i τ = 0 , T ¯ ∃ ( x l , i , t + τ r q − x l , i , t + τ ( r q , o p ) ) ⇒ P M G$
(24)

When analysing the situation and structuring the problems, past and present shortcomings in business process management are compared, as well as the causes (factors) of these shortcomings, errors, deviations and problems recorded in the past and present. At the same time, based on the previously formulated statement that the greatest and longstanding effect in improving business processes can be achieved by affecting the “root” causes, they are distributed by levels with the obligatory indication of “root”. The least effect is expected from level 1 causes, that is, those which are directly related to the deviation, the negative event and are not a consequence of other factors.

Association rules (17-24) for causing PMG pro-cedures of the analysis of deviations and situations, search of the reasons, problem structuring, information verification and adjustment of targets can to change and reproduce alternative methods of measuring indicators, determining deviations and their unacceptable values. New visions and approaches to the management of economic objects are pushing to rededermine these rules. In the course of data processing, deviations are calculated, non-compliance of parameters and disagreements among interested parties are revealed. In case of excess deviations and parameters’ exit from the acceptabl ranges, PMG is triggered, that is, the determination of goals as well as verification of control and normative values is initiated. Planning the main activity of the economic object includes the determination of target values of its production capacity and capacity of logistics chains (Thomas and Fellmann, 2009). To ensure high performance, it is necessary to identify and eliminate weak points both at the enterprise and in the supply chain in which it is included. To reveal such components, a set of factors that cause their emergence is determined and ordered. The obtained analytical results are used to argue for measures and projects to improve the overall structure of the enterprise and the supply chain. Improvement means support of the target or normative values of business processes and, above all, the intensities of production and flow processes.

Therefore, an important scientific and practical task is to imitate the flow process at the enterprise which takes into account the structure of the managed system, technology and sequence of process stages, factors and events that affect the intensity of these stages. Models of flow process allow to reveal “weak points” in it and the reasons for their formation that, ultimately, provides high level of efficiency and performance of the enterprise. The initial subject area for the search and elimination of “weak points” is the technological and organisational functional structure of the enterprise. The procedure for identifying and eliminating “weak points” is cyclical, since after improving the performance and quality of the component in the structure of the enterprise, which was a weak point, there is one or more other components that have a negative impact on the efficiency and performance of the enterprise. The problem of weak points in supply chain evolves in the similar way.

The procedure to eliminate “weak points” in the internal environment of the enterprise terminates only when the balanced state of its technological structure is reached, and is characterised by the equality or advantage of its throughput capability over the throughput capability of the entire supply chain. After triggering this condition, a similar procedure is carried out to identify and eliminate “weak points” in the supply chain, taking into account the particularities of economic connections in it. At the same time, it should be noted that due to the changes in the supply chain, any enterprise can be in the category of “weak point”, resulting in the fact that the management staff of this enterprise sets goals to achieve the compliance with the requirements of the supply chain as a whole, which is also largely based on the revealing and eliminating its own “weak points”. Modelling flow processes is carried out from the point of view of timely and adequate adjustment of intensity of processing working objects according to its desired values by means of reliable provision of jobs with necessary resources. The sequence of stages through which work objects (WO) pass and the transition conditions between these stages are usually represented in the form of a Business Process Model and Notation (BPMN) diagram (flow process models Design Structure Matrix F1).

It should be noted that WO is the dynamic es-sence of the elements over which actions (works) are performed, and resources are what these actions are carried out with. The process of WO processing consists of a certain number of W stages. The work performance at any separately taken w stage can be carried out in several “processing sites” $( w p h w )$ which are also classified as resources. This detailing is useful in cases where more than one “processing site” is assigned to more than one stage of the process. The structural model of a multi-stage procedure for WO processing in Business Process Model and Notation serves as the basis for development and implementation of dynamic models of this process to overcome management problems associated with deviations from target (desired or normative) values in terms of the volume of WO processing. With j-th management task $P j τ$ (managerial problem) in τ period of time, chains of actual circumstances $E i j$ and process indicators $S k ( j , i )$, which are indicators of these events and symptoms of the problem, and requirements $R l ( j , i )$ of interested parties – owners, staff, suppliers and consumers:

$〈 E i , S k , R l 〉 → P j τ$
(25)

Every inclusion of the work object into the sys-tem is $E t$ event, which causes the beginning of imple-mentation of technology of its processing. To monitor, analyse and model the flow of such objects, quantity indicators $A t i n$ of work objects that entered the system in t time period, and the intensity of their receipt $a t i n$ are used. Typical events, which are observed and managed in the system, initiate actions formalised in advance by the management staff of enterprise. Typical events include: receipts of WO (requests for its processing); WО transition to line; customer’s refusal to fulfill his request; lack of stored resources (raw materials, fuel, spare parts for equipment); achievement of the maximum level of use of resources (equipment, premises, vehicles, teams of workers); breakdown of simple resources.

The attraction of simple additional resources does not allow to fully eliminate the problem of floating weak points, which leads to low level of system load, insufficient intensity of the performance of orders as well as decrease of reliability and efficiency of technological processes. If to resort to increasing the stocks of stored resources, the turnover of working capital decreases and losses from overstocking increase. However, attributes can be assigned to each of these events when the typical event is no longer considered as such. For example, there can be a request for WO processing with a non-standard specification or equipment breakdown for an unknown reason. Besides, when considering the flow of typical events for some period of time or a set of events at the given point in time, managers find that deliberately established actions and algorithms do not allow to obtain predetermined results. They can not cope with the difficulty that has arisen, that is, with the problematic situation.

Formation or increase of Qw line at the stage $w ( w ∈ W )$ occurs in case of exceeding the number of WO over the value of throughput capability Mw at this stage (productivity, power, capacity of technological or logistic area). The occurrence of Qw lines before w stage provokes the threat of untimely execution of the full cycle of processing one and a set of WOs, increase of claims from customers, deterioration of the enterprise’s reputation, additional expenses for elimination of negative consequences and so on. The stage, which is characterised by the biggest average time of waiting for the line or the biggest average length $Q ¯ w ( τ )$ of such a line for τ period of time, is a sign of the presence of a “weak point” of BNP:

$B N P = w : ∃ m a x w { Q ¯ w ( τ ) } ∀ w ∈ W$
(26)

With $Δ M ˜ w , t$ deviations of Mw,t throughput capabilities, from $M w , t g o a l$ nessessary (desired) intensity, WO processing at each stage, taking into account the target value of the intensity of the whole $M P t g o a l$ flow process, these throughput capacities are adjusted. Diagnostics of functioning of structural elements of system and decision-making on adjustment of their throughput capabilities according to the established parameters is carried out through the approved ψ time interval. The cycle of the implementation of decision-making for w stage takes γw period of time $( γ w ≤ τ )$. Therefore, the throughput capability for w stage in each t period of time is calculated by the formula:

$M w , t = M w , t − 1 + Δ M ˜ w , t − 1 γ w = M w , t − 1 + M w , t − 1 g o a l − M w , t − 1 γ w$
(27)

Mw,t value at w stage, consisting of several processing sites, is determined as the sum of their throughput capabilities $( w p h , t w )$:

$M w ( h ) , t = ∑ h w p h , t w$
(28)

It can be assumed that the first processing site (h = 1) it can be used not only to perform works at the second stage (w = 2) but also at the third one (w = 3). Then

$w p 1 , t 2 = w p 1 , t 3$
(29)

that is, the same value of the maximum processing intensity at the specified site for the two stages is taken. But to calculate the value of the current volume of WO processing Zw,t, at each t period of time at w stage, an algorithm is determined for determining the number of WOs to be processed at one stage, taking into account the number of WOs at the processing site of the other stage. One of such algorithms is to use lies in the use of processing space first at w stage, and if there are free resources – at the w+1 stage:

$Z w , t = min = { M w , t + min [ w p h , t w − 1 , max ( 0 , M w − 1 , t − Z w − 2 , t ) ] Q w , t + Z w − 1 , t }$
(30)

The length of line dynamics is given as follows:

$Q w , t = Q w , t − 1 + Z w − 1 , t − 1 − Z w , t − 1 ∀ w > 1$
(31)

$Q 1 , t = Q 1 , t − 1 + A t − 1 i n − A t − 1 d e n − Z w , t − 1 ∀ w = 1$
(32)

where $A t − 1 d e n$ is number of refusals to process WO. To determine $A t − 1 d e n$ value, various methods can be implemented, in particular: based on a random distribution depending on the size of the line before the first stage or the number of WOs which are in the line in the system as a whole, or the expected duration of the entire WO processing cycle at the time of their receipt. An important analytical category is a reason, and at the same time, to substantiate management decisions on attracting, distributing and using resources to change the throughput capability of the system and ensure a high level of performance, it is important to identify a number of reasons $〈 C u 〉$ which impede or reduce the efficiency of the implementation of these decisions. The event, as a result of the impact of the external environment, and as a result of the implementation of the decisions taken by the enterprise is caused by one or many reasons that differ in content and nature of origin. Causes can be manifested simultaneously, periodically and irregularly. At the same time, the cause can be the result of the successive manifestation of other causes:

$C L ( u ) : C u − ς − 1 ... C u − 1 → C u$
(33)

The determination of the equation (33) is considered to be complete when identifying the “root” causes $〈 C u r o o t 〉$. Without their elimination, it becomes difficult or impossible to ensure the necessary efficiency of management processes. Thus, many causes of management problems can be expressed in the form of a dynamically distributed and logically streamlined sequence of events. In addition, it is important for the management process to tracking time lags between these events (causes) because to develop solutions, respond to individual events or to a number of events (situation), it is necessary to know the time reserves:

$Δ V T ( T g , T g + 1 )$
(34)

where $T g = C u ∼ E i$ is the moment of triggering u-th cause or the occurence of i-th event. It should be noted that causе-and-effect relationships can be established between two events and two indicators $e ( E i , E l )$ and $s ( S k , S k + 1 )$. However, two events consecutive in time do not exclude both cases: the presence and absence of such a relationship $e ( E i τ , E l τ + 1 ) , ( i ≠ l )$. “Cause-and-effect” pair has relative stability for two indicators within one period $s ( S k τ , S k + 1 τ )$ or given the delay $D T : s ( S k τ , S k + 1 τ + D T )$. Causе-and-effect relationships between events $e ( E i , E l )$ are determined by means of associative rules on type “if ..., than...”, while the relationships between indicators $s ( S k , S k + 1 )$ characterised by the rules of the type with the increase of Sk1 indicator increases (or decreases) Sk2 indicator. Moreover, in the general set of events, one subset is pointed out, in which incident relationships are traced between the events $e i φ ( i , φ ∈ I )$:

$e i l = ( E i , E l ) = { 1 , E i ≺ E l 0 ,$
(35)

To identify problems, data of the control of meeting the requirements of different subjects is used $N , n ∈ N$. Events $E i ( Δ R l , n n e g )$ associated primarily with the violation of these requirements can be the “root” cause of low efficiency and performance of the enterprise. The requirements of consumers are priority for the enterprise. At the same time, production, sales, supply and logistics departments at the enterprise form the pairs “supplier-customer”, which are characterised by the principle of priority and customer requirements.

The obvious requirements are laid down in “7p” logistics principles: high-quality products are needed in the right quantity at a reasonable price at the right time and place with minimal expenses for delivery and storage. In total, the same combination of non-compliance with the requirements of interested parties can cause a number of events to occur. Support of activity of the enterprise or a supply chain at high level of efficiency demands their determination in the general structure of “weak points” reducing the intensity of flow processes, their formation and identification of the reasons. Moreover, it is necessary to select indicators that, when tracking events in the flow process, signal the occurrence of these problems. These principles are applied to the development and structural imitation models of multistage flow processes.

Therefore, improving the efficiency and performance of the enterprise is one of the main directions of ensuring the competitiveness of the enterprise, since it covers the tasks of maintaining high-quality execution of orders. Synchronisation of processes and works on processing the flow of work objects, management of productivity and throughput capability of logistics components, planning the expenses for the acquisition of resources and updates play an important role in this process. The analysis of the efficiency of managerial decisions to overcome problematic situations and improve the reliability of processing the flow of work objects, and the performance of enterprises based on the implementation of imitation models. Perspective directions of development of imitation modelling of procedure for processing from the flow of work objects are formation of algorithms of distribution of these objects by sites of processing, they are common for several stages, as well as strategies for adjusting production capacities and throughput capabilities. The methodological aspects will be investigated and methodological provisions for the use of imitation models in the management of the working capital enterprise will be formulated focused on improving the overall efficiency of its activity during periods of time of different duration.

Increasing the efficiency through improving the processes of management of current assets requires the cost evaluation of key indicators of the evaluation of production, sales and logistics processes. First of all, those indicators are selected that reflect the quality of order execution and quality of customer service in the dynamics. The main principles and criteria in the management of current assets are decrease of current assets cost; reduction of losses due to deviations from the actual values of current assets of their nessessary values; ensuring a high level of financial stability. According to the system of balanced indicators proposed By D. Kaplan and G. Norton, the parameters of improving the efficiency of mmanagement of current assets are: stocks of commodity and material values; sales volumes of finished products; shortage of finished products and volumes of lach of materials; cycle of money (Kaplan and Norton, 2003). In system and dynamic and discrete event models, the following types of working capital are taken into account:

• R1 – raw materials;

• R2 – semi-finished and unfinished products;

• R3 – decrease or increase of expenses;

• R4 – inventory and accessories of products with a short service life;

• R5 – finished products.

System and dynamic models of activity of the enterprise are applied for substantiation of adjustments of throughput capabilities of production sites and logistic enterprises, and planning the aggregated movement of working capital, which along with technological resources (equipment, premises, vehicles, etc.) are involved in ensuring the necessary volumes of throughput capabilities in the production, sale and supply of products. Aggregation is carried out in the following directions: stock keeping units are combined into one or more types of products; product components – into products; time periods become larger; productivity of equipment (machines, technological sites) turns into the intensity of the material flow; stocks on stock items are summed up in stocks of finished products. The volume of consumer orders creates the need for the shipment of finished products which is provided at the expense of stocks of finished products and current production output. Each job within the production and logistics processes at the enterprise and in the supply chain should meet the needs for production output, movement of material flows and services. The description of these variables is provided below.

PO is throughput capability of the technological site in t time period:

$p o = ( Re g _ p o − W ) × d t$
(36)

where W is the rate of decrease of throughput capability of the technological site due to the deterioration of capacity and the disposal of production resources:

(37)

Reg_PO is the rate of the regulation of throughput capability:

$Re g _ P O = D E L A Y M T R ( D i f _ P O _ D , T i m e _ Re g , 3 )$
(38)

where Time_Reg is period of time for the adjustment of throughput capability; Constant_2 is average period of disposal of production resources; Dif_PO_D is the difference between necessary intensity of production or processing the material flow of the current capacity of throughput capability:

$D i f _ P O _ D = M A X ( ( S a m p l e _ D e m a n d − S a m p l e _ P J ) b 1 , ( S a m p l e _ P J − S a m p l e _ D e m a n d ) × ( − b 2 ) )$
(39)

where Sample_Demand is necessary intensity of production or processing the material flow; Sample_PJ is the value of throughput capability which is established for a certain planning period; b1,b2 are regulation parameters. In aggregated planning, there is a distribution of capacity between producing different types of products over a long period of time, the data of which is used in making the detailed operational plans for production output. The analysis of efficiency of the aggregated plans is carried out on the basis of system-dynamic models of activity of the enterprise, while the analysis of the efficiency of detailed operational plans is based on discrete event model. In discrete event models of enterprise functioning, raw materials R1 are described by quantitative characteristics:

SMr,t is volume of r-th type of raw materials at the period of time $t ( r = 1 , R , t = 1 , T ¯ )$;

$S M r , 0$ is quantity of each type of raw materials at the beginning of the analysed period.

It is necessary to take into account the type of supply of R-th type of raw materials:

$S T r = { 1 , r 2 , r 3 , r$
(40)

If a resource is purchased, ROPr purchase mechanism and BLTr period of time for the procurement are used. If a resource is produced at the enterprise, PPr production plan is used given MLTr production cycle. In the latter case, the mechanism for the arranged filling a resource at the expense of internal and external sources is used RPPr given internal and external sources BLTr and MLTr is used. R1 can be described by the following set of values:

$R 1 : 〈 S M r , 0 , S M r , t , S T r 〉 ⇒ 〈 S M r , 0 , S M r , t ( R O P r ∧ B L T r ) ∨ ( P P r ∧ V L T r ) ∨ ( R P P r ∧ B L T ∧ V L T r ) 〉$
(41)

BLTr value is considered as an external factor, which the company can partially affect through the implementation of management measures, for example, change of supplier, change of delivery method. However, there can be a situation when this factor is not amenable to adjustment at all. Regulation parameters in ROPr procurement management mechanism, which implement traditional stocks management strategies, are VSr,t procurement volume, $T r V S$ procurement period and SIr safety stock amount. The sources of improving the efficiency of management of current assets lie in the plane of interaction with affiliated trading enterprises (distributors and dealers) and consumer enterprises. The production enterprise sells its products in two ways: direct sales to customers (direct sales) and sales through the distributor and his distribution network. In direct sales, the total number of consumers is divided into two classification groups. The first group is regular customers with whom longstanding contractual relations are established, and some of them are focused on cooperation and partnership. The second group includes consumers with irregular or-ders.

Thus, discrete event model of the main activity of the enterprise includes three flows of orders – from two groups of consumers and affiliated merchants. Order flows have the following variables: 1) interval between successive receipts of orders (k-1)) and k, carried out by consumers of c-th group COIk,c,t (c = 1,3 is the consumer group index); 2) volume of k-th order from consumers belonging to c-th group, COVk,c,t at t period of time.

## 4. CONCLUSIONS

Therefore, discrete-event models of enterprise functioning are used for detailed analysis of the efficiency of the movement and use of working capital during the operating cycle (the average period between the purchase of raw materials and receipt of sales revenue) with given throughput capabilities of technological sections of the production and logistic system which are determined in the aggregated plans of the enterprise’s activity. Imitatation models in the aggregated and operational analysis and planning the enterprise’s activity allow to determine the dynamics of sales in kind and value terms (sales revenue) for the entire period under research, as well as the current, total and average value of the volume and value of working capital for the period. On their basis, the indicators of financial evaluation of the efficiency of the use of production resources and working capital management are calculated: indicators of volume, profit and profitability of core activity, production and sales; turnover coefficient of current assets (asset turnover); coefficients and periods of turnover of material working capital, finished products, receivers and payables, coefficient of transformation, etc.

However, imitation models include a set of marketing and logistics indicators, which allows to evaluate the efficiency of the processes of sales of finished products and customer service. The joint use of heterogeneous performance indicators of the enterprise allows to more accurately evaluate the situation and substantiate adequate management decisions with the help of imitation models reflecting the possible scenarios of its development with and without these decisions during periods of time of different duration. Thus, between aggregated planning and operational volume-calendar planning (dispatching) in practice, as a rule, there is a gap, so an important methodological issue is to ensure the balance of data and its exchange between two levels of planning.

## Table

Template for calculating the integrated evaluation of the economic object’s overall efficiency

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