The aim of the article is to develop a model for managing business processes in the information service based on behavior of the company. The main business processes of the company were identified, and their main interrelationships were reflected at the conceptual level. A model in the Powersim Studio 7 simulation environment is presented, which allows regulating the interaction between companies in the information service, identifying bottlenecks in the company's business processes, and predicting the total income of an enterprise depending on various market conditions.
In the modern world, in the context of growing informatization and general globalization, the economy has received new opportunities on the Internet. Thanks to the latest information technology, economic activity becomes more efficient and profitable. In the context of digitalization of business processes, the issue of interaction between companies using information services and, as a result, the emergence of cloud resources for collecting, processing, and storing data (Data Processing Centers
Such centers are a promising area of business development and a convenient tool for companies to
interact with users. Business process management of such data centers is based on business analysis
and technical specifications, which are not related to each other. Therefore, an approach is needed that
would be based on an assessment of the entire architecture of the company, and not on its individual
levels. It is system-dynamic modeling [
This article proposes to use the system-dynamic approach for the analysis of activities of an information service on the example of the Data Processing Center (DPC) of Mail Ru Group (Russia).
Interaction information services refer to the B2B e-business model focused on the business of corporations that act as both sellers and buyers. They cover a wide range of applications that help businesses build electronic relationships between distributors, resellers, suppliers, and partners. These services give businesses access to information about a product, customer, supplier, transportation, storage, supply chain, competitors, marketing, and sales. Using the toolkit of B2B applications it is possible to re-engineer the supply chain and partnerships. However, the presence of many partners / customers in the chain of business processes of such information services does not make it possible to clearly define or predict the effect of interaction in advance.
This work for the first time proposes to use the system dynamics method for analyzing and predicting the data in information interaction services that allows, during experiments, to identify hidden factors affecting business performance, and helps to improve the decision-making process.
The article examines the activities of an information service using the example of the Data Processing Center (DPC) of Mail Ru Group, which implements its services through e-business tools. The company has partnered with other e-commerce businesses that are building next-generation data center software. Interaction with other electrical parts engaged in other activities is seen as an important role in the transport sector.
Mail Ru Group's business process model is based on the e-business customer service model. The conceptual diagram of the future model is shown in Figure 1: Mail Ru Group service delivery diagram.
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While building a model on this basis some of additional factors must be fulfilled. Due to the specifics
of the market in question, there is a serious competition between a small number of competitors, which
necessitates significant marketing costs, which can vary depending on the circumstances. Also, due to
the fact that the company operates mainly in the B2B sector, the issue of partnership with other
enterprises engaged in the production of software products in the field of e-commerce is extremely
relevant for it. And, due to the high requirements for the operation and maintenance of equipment, Mail
Ru Group is forced to allocate a large amount of funds for the reproduction of fixed and circulating
assets. An important factor in the market for the provision of data center services is the degree of
customer confidence, which is due to the degree of security of access to stored information, and
uninterrupted access to it [
Having considered the specifics of the subject area and building a diagram of cause-and-effect
relationships, you can immediately start developing a model of the company's business processes using
the Powersim 7.0 software product and system dynamics tools, taking into account the interaction of
companies [
The task of this model will be to determine the volume of the company's total income, depending on various factors, such as interaction with freelancers, abandonment rates and changes in tax rates.
2.1.
The general view of the block is shown in Figure 2: General view of the block "Data Center Business
( ) = ( 0) + ∫ 0
, t = 0. . ,
Salary refund cancel
Number of customers
Income tax Freelancers Salary interaction with companies
utflow UnforeseenCosts_O contingency costs Pledged Advertising costs
Unforeseen costs Profit from sales Unforeseen costs
Return of unused
funds interaction with
companies Profit from sales Number of customers
Advertising costs ( ) +
− ∫ 0
+
Number of customers is determined by the formula: = ( ∗ + ∗ ) ∗ Number of corporate clients is determined by the formula: = { 0, , ≤ 0 = 5000 +
/30000, = 1000 + 0,1 ∗
/50000), ∗ (0,25 ∗ = { + | , ∗ |,
+ > 0 Refunds in connection with the cancellation of services are determined by the formula: Unforeseen Costs determined as: ∗ ), (1) (2) (3) (4) (5) (6) (7) (8)
The "Unforeseen costs" block is shown in Figure 3: Diagram of the block "Unforeseen costs".
Pledged contingency costs are determined by the formula: ( ) = ( 0) + ∫ 0
The receipt of costs for solving non-staff problems with the data center (UC Inflow) is determined The costs incurred during the overhaul of the data center (General Costs) is determined by the = (1 − ) ∗ ( + + ),
( ) = ( 0) + ∫ 0
The outflow of funds spent on an advertising campaign (Adv_outflow) is calculated using the by the formula: formula: , , , , (9) (10) (11) (12) (13) (14)
Thus, having identified all the elements of the model and developing its mathematical model, one can proceed to the system-dynamic modeling of the process of functioning of the data center Mail Ru
The simulation period is 12 months, since it is not feasible to simulate for more than one year in today's constantly changing conditions in a dynamic e-commerce market. The modeling step is 1 month.
1) when working with freelancers, sales profit increases, but the company pays salaries; 2) the company does not interact with freelancers and do not receive addition income from sales.
The interaction switch is shows in Figure 5: Switch "Interaction with companies", and the "Return percentage" slider with a value of 0.01, or 1% is shows in Figure 6: "Percentage of Return" regulator.
Figure 6 shows. In most cases, a customer placing an order for the use of a data center is firmly convinced of his intentions, and he can only cancel the order under unforeseen circumstances. In addition, this indicator also takes into account the return of the order associated with the inadequate quality of the data center.
The forecasting using this model is carried out based on the analysis of the dynamics of changes in key indicators.
We can consider several states of business, setting different conditions of interaction, presented in Table 1, and the results of the experiments 1-4 in: Table 2, Table 3, Table 4, Table 5.
Modelling has shown that the system is not homogeneous, and it is difficult to find a single solution for problems arising under different conditions.
interaction with companies
Without interaction With interaction 0,1 0,2 0,3 0,4 0,5
The results show that when the company interacts with freelancers, and the share of DPC overhaul costs, taxes, and order returns is reduced, the company's financial performance improves. Experiment 1 is an optimistic scenario for the company's development. But its conditions are too ideal: active interaction with freelancers, no capital repair costs, a low tax rate on advertising (5%), a low percentage of order returns (5%). This situation is practically impossible. Therefore, the best from the point of view of company's development is experiment 3, which provides profit growth. The set values of experiment 3 are: interaction with freelancers, the need for a DPC overhaul, advertising tax - 5%, order return rate - 15%. In the whole, the model showed the significance of each indicator and the nature of its impact on the company's financial performance.
The article comprehensively examines the features of business processes of the information service of interaction on the example of the company Mail Ru Group. In current conditions, the use of such tools can significantly increase the profit of an enterprise, and the specificity of e-business is such that interaction with other enterprises in the same industry can significantly increase the efficiency of the company.
To model of the company's business processes, a system-dynamic approach was applied, and a diagram of the cause-effect relationships of Mail Ru Group was built, and the functional relationships are reflected at the conceptual level. A model of the company's business processes was developed, considering the interaction of companies. With its help, the analysis and interpretation of the simulation results in four different states of the system were carried out. Thus, the proposed system-dynamic model of enterprise business processes is suitable both for finding disadvantages in the company's business processes and for predicting total income depending on various market conditions.