Simulation and optimisation of business process management: Case study of IT company

Serhiienko, Olena; Maščenko, Maryna Anatolіїvna; Samorodov, Borys; Babichev, Anatoliy; Klimenko, Olena Article Simulation and optimisation of business process management: Case study of IT company Business Systems Research (BSR) Provided in Cooperation with: IRENET - Society for Advancing Innovation and Research in Economy, Zagreb Suggested Citation: Serhiienko, Olena; Maščenko, Maryna Anatolіїvna; Samorodov, Borys; Babichev, Anatoliy; Klimenko, Olena (2024) : Simulation and optimisation of business process management: Case study of IT company, Business Systems Research (BSR), ISSN 1847-9375, Sciendo, Warsaw, Vol. 15, Iss. 1, pp. 67-90, https://doi.org/10.2478/bsrj-2024-0004 This Version is available at: https://hdl.handle.net/10419/318832 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ 67 Business Systems Research | Vol. 15 No. 1 |2024 Simulation and Optimisation of Business Process Management: Case Study of IT Company Olena Serhiienko, Maryna Mashchenko Department of Business, Trade and Logistics, National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine Borys Samorodov Department of Banking Business and Financial Technologies, V. N. Karazin Kharkiv National University, Kharkiv, Ukraine Anatoliy Babichev Department of Management and Administration, V. N. Karazin Kharkiv National University, Kharkiv, Ukraine Olena Klimenko Department of Public Administration and Political Economy, Simon Kuznets Kharkiv National University of Economics, Kharkiv, Ukraine Abstract Background: In managing business processes of complex hierarchical systems, primary attention is given to analysing, accelerating, and optimising the basic processes typical for any company. Objectives: The goal of this work is to prove that while managing business processes, it is crucial to consider the peculiarities of the external and internal environment to determine the effects of individual triggers. Method: An example of business process analysis was provided regarding the peculiarities of managing IT service companies operating in a dynamic environment of rapid technological changes. The business processes analysis of IT service companies in Ukraine was conducted. Business process groups characterised by low use of labour and financial resources and excessive and high levels of risk management were determined. Results: An algorithm for optimising the IT company's business processes was developed. Simulation and optimisation models for managing IT company business processes were developed using scenario modelling and simulation techniques. Conclusion: Based on these models, a predictive evaluation of management impacts on business processes was conducted, representing individual clusters according to defined management strategies. Keywords: business process; cluster; management simulation model; business process activities JEL classification: С53, С61, В21 Paper type: Research article Received: 8 Mar 2024 Accepted: 29 May 2024 Citation: Serhiienko, O., Mashchenko, M., Samorodov, B., Babichev, A., & Klimenko, O. (2024). Simulation and Optimisation of Business Process Management: Case Study of IT Company. Business Systems Research, 15(1), 67-90. DOI: doi.org/10.2478/bsrj-2024-0004 68 Business Systems Research | Vol. 15 No. 1 |2024 Introduction The article studies the peculiarities of modern concepts and ideas regarding managing the development of complex systems. These represent a complete object consisting of functionally diverse but connected by functional subordination to achieve the set goals. Similar management objectives are widespread at this stage of the development of economic systems. These can be corporations, multidisciplinary enterprises, and even organisations that provide regional interaction within one country. The needs of the modern dynamic market require reviewing the life cycle of products and services while maintaining the quality of the final product (Stark, 2022). That causes a contradiction in the management of the company's development because it forces the companies to make radical changes to the strategic development plans of enterprises (Kopei et al., 2023). The management concept relies on the company management paradigm as a framework, which can be adapted, in this case, to meet the specific needs of project management in response to changing circumstances (Soleymani, 2020). Nevertheless, the newer information, knowledge and skills become available to the enterprise, the more demands society has for the final product, and vice versa. Such a situation begins to make adjustments to management processes, and an unchanged management paradigm, i.e., the use of old methods and models in new fast-moving conditions, can lead not only to a significant lag in competition but also to the complete collapse of the business. Most modern organisations are hierarchical systems operating in conditions where information is the central resource, and the economy has a network structure. The organisation's external environment acts as a broadcaster of information that has a targeted impact on forming the final product. It orients the organisation to change or improve its management structure into a group of interconnected blocks that aim to implement a single strategy in modern informatisation conditions (Webler, 2022). On the one hand, such “blocks” are easier to manage and have sufficient flexibility. On the other hand, this causes additional informational noise, which can hinder the timely detection of any problematic moment. At the same time, flexibility advantages can become an obstacle in coordinating resources, but they allow single-out individual management processes and exert a targeted influence on them. The abovementioned is especially typical for companies working in the field of information technologies (IT). The IT industry generally finds it difficult to harmonise with the classical management paradigm based on the rational production organisation to obtain the maximum additional value. The “maintenance-development” cycle does not coincide with the life cycle of IT companies' products and services since they are oriented to the “innovation-development” cycle. In this case, the “maintenance” step is replaced by an innovative step, which does not simply save the work result but updates it and brings it to the level of obtaining a new version or a significantly new product according to the efficiency criterion (Guo et al., 2020). Each step is a separate business process (BP) (Mahdiraji et al., 2020) because the product is being refined and value is added. An essential ability of modern organisations is a flexible and effective response to unexpected events (Röglinger еt al., 2022). Critical events can be caused by a lack of resources, including financial (Goel et al., 2021) or human (Lee et al., 2019), which in turn can be caused by an incorrect distribution or sales management approach (Kajba et al., 2022). Researching this aspect in the example of IT companies in China (Ilmudeen, 2022) revealed a positive and significant relationship between marketing turbulence, flexibility and innovation potential. Technology innovations can soften the impact of marketing turbulence by changing how companies’ function. This shift often 69 Business Systems Research | Vol. 15 No. 1 |2024 requires companies to focus on product promotion and sales to drive innovation. The above can be studied as an example of a modern direction in IT service companies as blockchain platforms. For example, the Ethereum and Caterpillar platforms allow individuals to handle their business processes independently without relying on a central authority for transactions. Such functions are basic blocks for performing joint business processes between the parties. A blend of trusted Business Process Management Systems (BPMS) that rely on the widely used Business Process Model and Notation (BPMN) standard is utilised to minimise errors, which in turn increase organisational performance (Suša Vugec et al., 2020; Slavec et al., 2023; Dwivedi et al., 2021). This approach enables the creation of convenient abstractions, which, in turn, facilitates the quick development of process-oriented software programs (Lpez-Pintado et al., 2019). Something similar applies to the management processes regarding the Internet of Things (IoT). The IoT-based business model improves overall capabilities but has several challenges regarding the accuracy of business asset information and difficulty in requirements analysis. All this leads to the need to manage a large volume of data. It is common practice to break down extensive processes into smaller sub-processes to increase efficiency and prioritise the most critical aspects of a business. This helps to minimise any potential issues that may arise (Shoukry et al., 2021). The study aims to present the methodological foundations of creating a paradigm for managing the development of an organisation as a complex hierarchical system operating in a rapidly changing external environment. Throughout the study, we examine the peculiarities of structural changes in business process management as they undergo optimisation. The given optimisation model allows considering a separate BP through subsidiary processes. On this basis, a simulation modelling method is proposed, which allows considering the future consequences of decision-making at the current moment within the limits of business processes at all levels. The article reveals the necessity of studying the complex properties and business process optimisation of a complex hierarchical system through their detailing. This enables the identification of the optimisation model's variables and their use as controlling influences in managing individual triggers. The article is structured in the following way. Section 2 provides the aim formalisation, criteria and limitations in managing a complex system, which allows the writing down the structure of each BP according to the function of efficiency and details of business processes in a complex hierarchical system concerning IT service companies, as the object of research. Section 3 presents the simulation results with the development of optimisation model flow charts. Section 4 describes the obtained results and measures that can be offered to companies with a complex hierarchical management system to optimise individual BPs. Section 5 presents the conclusions of the work. Methods Formalisation of the aim, criteria, and limitations A system is a set of means that create a specific structure to achieve a particular goal efficiently. By formalising a complex hierarchical system of organisation according to the above definition, it is possible to operate with three categories: element, relation, and property. The complete specification of these categories will determine the organisation system through its development. The representation of M elements, the relations between them R, will determine the universe of system properties P: 𝑃=𝑀×𝑅 (1) 70 Business Systems Research | Vol. 15 No. 1 |2024 and the Cartesian product 𝑆=𝑀×𝑅×𝑃 (2) Determine the set of objects and their inherent phenomena concerning the complex hierarchical system S. It follows from the expression (2) that a specific complex hierarchical system of the organisation will be uniquely determined only in the case when given subsets of the elements of M = {m1, … mi}, relations between them R = {r1…rj} and properties Р = {p1…pk}. At the same time, the specified sets are finite and can be described informatively when the level of detail of the system elements is determined. A system with properties P can be obtained in development management only if the set S is not empty. That is, for equation (1), the universe of the system will include 𝑃⸦𝑀×𝑅 (3) which indicates the existence of such a subset of elements M and relations between them R on which the development of this complex system is possible. A hierarchical system may contain several specified subsets, which indicates a multi-vector paradigm for developing such systems. Nonetheless, the general concepts (1) - (3) enable us to consider this process discretely, by separate vectors. Mathematical representation of a complex hierarchical system Consider the set S as a complex hierarchical system consisting of nodes that interact with each other but are, to a certain extent, independent. In the general cycle of goods or services production, they can create delays, change, or recover. In the specified system, some triggers of these processes can occur randomly. Perturbations in such a system are insignificant to a certain extent. The system is deterministic if the parameters are unchanged (Xing et al., 2019). However, disturbances that will lead to a change in parameters can cause not only the stoppage of a separate node but also problems in managing the entire system (Chueshov & Schmalfuß, 2020). Consider a random process in some system node. Assume that this process occurs in a discrete phase space: ℰ={0,1,2,…} (4) A number of time points of the system transition from one state to another is also discrete: 𝑇={0,1,2,…} (5) Consider the process specified at the node through a random variable corresponding to the number of the state where the system is at the moment of time ℓ. Denote through Eℓi the state of this node is summarised because, at the moment of time ℓ the system is in a state of impact і to the specified separate node: 𝐸𝑖ℓ∞(𝜉ℓ=𝑖) (6) A complete theoretical-probabilistic description of the system evolution control development consists in determining the probability that for arbitrary time sets ℓ1, ℓ2…ℓk (ℓ1<ℓ2<…<ℓk) for separate nodes of the system and the effects on these nodes from the side of the system і1, і2…іk the occurrence takes place: 𝐸ℓ1ℓ2…ℓ𝑘,𝑖1,𝑖2,…𝑖𝑘=𝐸ℓ1𝑖1∩𝐸ℓ2𝑖2∩…∩𝐸ℓ𝑘𝑖𝑘=⋂𝐸ℓ𝑡𝑖𝑡 𝑘𝑡=1 (7) Thus, at a given k moments of time, the S system exerts a specific management influence on separate nodes, which generally forms a paradigm for developing the entire hierarchy of individual organisational elements. The probability of the event (7) can be calculated through the conditional probability system. At the same time, there is a class of random processes for which the necessary description can be obtained more simply. For example, this is a class of Markov-chain probability distribution (Munkhammar & Widén, 2018), which can be considered flexible models of individual business processes with varying management models depending on the situation. 71 Business Systems Research | Vol. 15 No. 1 |2024 Such modelling can be carried out using Vensim Front Page tools, which allow the building of flexible models with a flexible distribution of resources concerning managing a complex system. Analysis of the company's business processes according to the optimality criterion Consider managing the development of a complex system S according to the optimality criterion. Then, each node acts as a subdivision n that uses m types of resources (raw materials, energy, labour) for its work. The matrix of resource-specific costs for producing goods or services is known: i=1,...,m – resource number; j=l,...n – a sign of a subdivision performing some BP N. If the volumes of all available resources bi and prices сj (profit rates) for each product or service are known, an optimal plan for performing works/services can be drawn up. For this, the company's work can be represented by a vector of variables xj: x1, x2, ...xn, describing the amount of work performed. The company's total income ∑𝑐𝑗𝑥𝑗 𝑛 𝑗=1 will be the sum of the profits of individual subdivisions сj xj according to their contribution to the formation of profit in the general business process N. Then, the costs for each type of resource will be: ∑𝑎𝑖𝑗𝑥𝑗 𝑛 𝑗=1 𝑖=1,…𝑚 Moreover, the optimality model will look as follows: 𝑓(𝑥1,𝑥2,...𝑥𝑛)=∑𝑐𝑗𝑥𝑗 𝑛 𝑗=1 →𝑚𝑎𝑥 (8) At the same time: ∑𝑎𝑖𝑗𝑥𝑗 𝑛 𝑗=1 ≤𝑏𝑖 𝑖=1,2,…𝑚 (9) i.e., general resources cannot exaggerate available volumes, and 𝑥𝑗≥0 𝑗=1,2,…𝑛 (10) which denotes the participation of each separate company division in implementing production activities according to the business process N. The problem (8) can be presented linearly: 𝑓=𝑐1𝑥1+𝑐2𝑥2+...+(𝑚𝑖𝑛) (11) where the constraint system is expressed as follows: {𝑎11𝑥1+𝑎12𝑥2+⋯+𝑎1𝑛𝑥𝑛≥(≤)𝑏1 𝑎21𝑥1+𝑎22𝑥2+⋯+𝑎2𝑛𝑥𝑛≥(≤)𝑏2 ………………………………… 𝑎𝑚1𝑥1+𝑎𝑚2𝑥2+⋯+𝑎𝑚𝑛𝑥𝑛≥(≤)𝑏𝑛 when performing (10). Problem (11) will be a classic optimisation problem based on the conditional extremum of many variables' functions (Kimiaei et al., 2022). Such an approach makes it possible to identify business processes that are the basis of the company's profit. However, it is difficult to adjust due to the inability to dissect tactical and strategic business processes at the level of a separate structural unit of the company, which is a hierarchical system. Changing the business process management system (BPMS) structure requires adjusting the set of models that describe the functioning of a complex system, considering the levels of hierarchies. In this case, it is possible to calculate the total efficiency of tactical and strategic business processes through subsidiary processes. Thus, a shift in the assessment criterion from optimality to the efficiency of a separate process is possible. Management of the company's processes according to the efficiency criterion Based on the research of BusinessNews Publishing (2014) and Ilmudeen (2022), the overall assessment of the IT service company's strategic business process effectiveness 72 Business Systems Research | Vol. 15 No. 1 |2024 depends on the efficacy of each subsidiary BP. That is, the BPMS centre's effectiveness in the IT service company is determined by considering the effectiveness of all other system elements: the purpose of the BPMS operation is to achieve the maximum level of strategic BP efficiency. Therefore, the effectiveness of the IT service company's entire BPMS begins with the efficacy of the lowest-level activities and business processes. Considering the accepted hierarchical structure of the BPMS, the lowest level of consideration is BP's operational level. It is proposed that the effectiveness of the operational-level BP be evaluated concerning the amount of labour and material resources spent on the business process. Figure 1 displays the general mechanism for assessing the efficiency of business processes in the IT service company. Figure 1 Mechanism for assessing the efficiency of business processes in the IT service company Source: Authors’ work II stage - Building BP efficiency assessment models using production functions 2.1. Assessment of model parameters and their statistical significance 2.2. Assessment of model adequacy, coefficient of multiple correlation 2.3. Assessment of the model's statistical significance by the Ftest I stage - Economicstatistical assessment of the BP quantitative parameters 1.1. Assessment of the labour resources cost for the BP implementation 1.2. Assessment of the material resources cost for the BP implementation 1.3. Assessment of BP implementation results III stage - Assessment of BP management effectiveness indicators 3.1. Assessment of the average resource productivity 3.2. Assessment of the marginal resource productivity 3.3. Assessment of the BP results elasticity in terms of resource expenditure 3.4. Assessment of the marginal rate of resource replacement 3.5. Assessment of the efficiency of higher levels BPs based on the performance indicators of subsidiary BPs IV stage - Assessment of the synergistic effect from the implementation of subsidiary BPs V stage - Multidimensional statistical analysis of business processes by performance indicators 5.1. Clustering of operational-level business processes by performance indicators 5.2. Determination of the BP type by the level of its efficiency 73 Business Systems Research | Vol. 15 No. 1 |2024 Ten leading IT service companies in Ukraine were reviewed using the specified mechanism (Figure 1) and considering approach (8). According to the State Statistics Service of Ukraine, their list and performance indicators for 2022 are shown in Table 1. Table 1 List of leading IT service companies in Ukraine Company name Net income in 2022, million USD EPAM Systems 625.0 GlobalLogic Ukraine 356.0 Luxoft Solutions 184.0 Ciklum 149.0 Intellias Institute of Information Technologies 126.0 Infopulse Ukraine 104.0 LOHIKA LTD LLC 93.0 Sigma Software 61.0 Grid Dynamics Ukraine 51.0 Astound Commerce 46.0 Source: According to data from the State Statistical Service of Ukraine (n.d.) To better understand the impact of business processes and resource allocation for each of the companies mentioned above, one can analyse them using the concept of production function. This helps to establish a clear relationship between input resources and output results (Sickles & Zelenyuk, 2019). Considering the rapidity of technology development in the IT industry, especially in the provision of service services, the Cobb-Douglas production function in the form of J. Tinbergen (Wang et al., 2021) should be chosen as a modelling tool in the study (Wang et al., 2021), which takes into account the impact of technological progress (Biddle, 2020). Result dependence characterisation of processes and resources for an IT service company In general, the mathematical model of the Tinbergen production function (Wang et al., 2021) can be represented by the expression: 𝑌=𝐴⋅𝑒𝜌⋅𝑡⋅𝐿𝛼⋅𝐾𝛽 (12) where: α, β – output elasticity by factors; A ⋅ eρ ⋅ t – the level of technical progress at A<0; ρ>0 – means the rate of technological development. The study used time expenditure (zp)and capital expenditure (zm) as production factors for BP's activities (actions) to build a dependency model. The result factor is the value of the integral assessment of the satisfaction level with the BP 𝑒𝑖𝑗𝑘 𝑡 results. Considering the above, the research used a general mathematical model for assessing the effectiveness of BP in the following form: 𝑒𝑖𝑗𝑘 𝑡=𝐴⋅𝑒𝜌⋅𝑡⋅𝑧𝑝𝛼⋅𝑧𝑚𝛽 (13) For the study, the effectiveness of BP was assessed using the Statistica software package in the Non-Linear Estimation module for a generalised complex hierarchical system of an IT service company. Table 2 summarises the results of building the obtained mathematical models into production functions. 74 Business Systems Research | Vol. 15 No. 1 |2024 Table 2 Results of modelling assessment of operational level BP efficiency BP designation BPs name A model for assessing the BP effectiveness d R F p-value А1 Marketing А1.1 Market research 𝑒11 𝑡=0.024⋅𝑒0.85⋅𝑡⋅𝑧𝑝11 0.087⋅𝑧𝑚11 0.891 0.77 0.877 964.8 0.0031 A1.2 Lead generation А1.2.1 Lead generation via company email 𝑒121 𝑡=0.19⋅𝑒1.13⋅𝑡⋅𝑧𝑝121 0.097⋅𝑧𝑚121 0.107 0.97 0.985 9666.67 0.00 А1.2.2 Lead generation via conferences 𝑒122 𝑡=0.215⋅𝑒0.93⋅𝑡⋅𝑧𝑝122 0.104⋅𝑧𝑚122 0.091 0.87 0.933 764.78 0.012 А1.2.3 Lead generation via the website А1.2.3.1 Promotion through search engines 𝑒1231 𝑡=0.233⋅𝑒0.83⋅𝑡⋅𝑧𝑝1231 0.084⋅𝑧𝑚1231 0.102 0.911 0.954 126.23 0.008 А1.2.3.2 Promotion via social networks 𝑒1232 𝑡=0.385⋅𝑒0.5⋅𝑡⋅𝑧𝑝1232 0.12⋅𝑧𝑚122 0.039 0.76 0.872 274.7 0.047 А1.2.4 Lead generation through a partner program 𝑒124 𝑡=0.27⋅𝑒0.71⋅𝑡⋅𝑧𝑝124 0.14⋅𝑧𝑚124 0.062 0.81 0.904 113.82 0.038 А1.3 Increasing brand awareness А1.3.1 Content distribution through thematic resources 𝑒131 𝑡=0.25⋅𝑒0.97⋅𝑡⋅𝑧𝑝131 0.112⋅𝑧𝑚131 0.07 0.788 0.887 347.21 0.005 А1.3.2 Content distribution to leads (potential customers) 𝑒132 𝑡=0.097⋅𝑒0.56⋅𝑡⋅𝑧𝑝132 0.082⋅𝑧𝑚132 0.522 0.825 0.908 965.83 0.027 А1.3.3 Mailing to existing contacts 𝑒133 𝑡=0.47⋅𝑒0.347⋅𝑡⋅𝑧𝑝133 0.21⋅𝑧𝑚133 0.074 0.76 0.87 77.6 0.022 А1.4. Content development 𝑒141 𝑡=0.089⋅𝑒0.745⋅𝑡⋅𝑧𝑝141 0.354⋅𝑧𝑚141 0.479 0.79 0.889 105.33 0.047 А2 Sales А2.1 Customer engagement А2.1.1 Customer engagement through a tender 𝑒211 𝑡=0.065⋅𝑒1.03⋅𝑡⋅𝑧𝑝211 0.107⋅𝑧𝑚211 0.604 0.81 0.9 119.36 0.029 А2.1.2 Customer engagement through open vacancies 𝑒212 𝑡=0.128⋅𝑒0.43⋅𝑡⋅𝑧𝑝212 0.04⋅𝑧𝑚212 0.642 0.837 0.915 143.78 0.028 А2.2 Contract signing 𝑒22 𝑡=0.116⋅𝑒0.453⋅𝑡⋅𝑧𝑝22 0.63⋅𝑧𝑚22 0.17 0.78 0.887 99.27 0.047 А2.2.1 Signing a support contract 𝑒221 𝑡=0.186⋅𝑒0.453⋅𝑡⋅𝑧𝑝221 0.53⋅𝑧𝑚221 0.24 0.91 0.954 283.11 0.019 А2.3 Preparation of the project start 𝑒23 𝑡=0.426⋅𝑒0.16⋅𝑡⋅𝑧𝑝23 0.24⋅𝑧𝑚23 0.23 0.94 0.97 438.67 0.009 А3 Negotiations А3.1 Pre-Sale 𝑒31 𝑡=0.355⋅𝑒0.312⋅𝑡⋅𝑧𝑝31 0.48⋅𝑧𝑚31 0.123 0.74 0.86 79.69 0.048 А3.2 Elaboration phase 𝑒32 𝑡=0.274⋅𝑒0.184⋅𝑡⋅𝑧𝑝32 0.19⋅𝑧𝑚32 0.25 0.757 0.87 87.22 0.042 А3.3 Upsales 𝑒33 𝑡=0.155⋅𝑒0.113⋅𝑡⋅𝑧𝑝33 0.41⋅𝑧𝑚33 0.42 0.803 0.896 114.13 0.033 А4 Project implementation А4.1 Project development 𝑒41 𝑡=0.268⋅𝑒0.77⋅𝑡⋅𝑧𝑝41 0.104⋅𝑧𝑚41 0.094 0.92 0.959 322 0.007 А4.2 Monitoring А4.2.1 Questionnaire РМО 𝑒421 𝑡=0.54⋅𝑒0.233⋅𝑡⋅𝑧𝑝421 0.18⋅𝑧𝑚421 0.054 0.72 0.849 61.7 0.049 А4.2.2 Project Statuses 𝑒422 𝑡=0.145⋅𝑒0.253⋅𝑡⋅𝑧𝑝422 0.187⋅𝑧𝑚422 0.46 0.879 0.943 194.18 0.027 А4.2.3 Status - meeting 𝑒423 𝑡=0.179⋅𝑒0.173⋅𝑡⋅𝑧𝑝423 0.23⋅𝑧𝑚423 0.411 0.69 0.831 62.32 0.047 А4.2.4 Delivery statusmeeting 𝑒424 𝑡=0.384⋅𝑒0.03⋅𝑡⋅𝑧𝑝424 0.14⋅𝑧𝑚424 0.2 0.71 0.84 68.55 0.042 А4.2.5 Process adjustment 𝑒425 𝑡=0.14⋅𝑒0.57⋅𝑡⋅𝑧𝑝425 0.081⋅𝑧𝑚425 0.322 0.95 0.975 532.22 0.007 А4.3 Support 𝑒43 𝑡=0.486⋅𝑒0.032⋅𝑡⋅𝑧𝑝43 0.18⋅𝑧𝑚43 0.12 0.88 0.938 205.33 0.036 Source: Authors’ work High-quality indicators characterise the resulting models. The evaluation criteria are the determination coefficient, the coefficient of multiple correlation, the F-test and its 81 Business Systems Research | Vol. 15 No. 1 |2024 Figure 5 Dynamics of the model values of the financial resources’ average productivity by project, unit/conditional units Source: Authors’ work Figure 6 Dynamics of model labour cost values average productivity by project, unit/hour Source: Authors’ work Figure 7 Dynamics of model values of the financial resources’ marginal productivity by project, units/conditional units Source: Authors’ work 82 Business Systems Research | Vol. 15 No. 1 |2024 Figure 8 Dynamics of the model values of the financial resources’ marginal productivity by project, unit/hour Source: Authors’ work Figure 9 Dynamics of model values of the efficiency average level of the project A3.1, units Source: Authors’ work Table 5 presents the assessment of the adequacy of the built simulation model for managing BP A3.1 using indicators of average absolute and average relative modelling error. Table 5 Assessment of the adequacy of the built simulation model for ВР managing А3.1 Indicator Denotation and obtained model values of the resulting model variables Average deviation A(zp)31 M(zp)31 A(zm)31 M(zm)31 SerE(A31) Average model values for the modeling period 0.750 0.360 0.053 0.007 0.795 - Actual values 0.724 0.348 0.054 0.007 0.79 - Absolute deviation, units 0.026 -0.012 0.001 0.000 -0.005 0.02 Relative deviation, % 3.52 -3.32 1.06 -6.25 -0.59 -1.12 Source: Authors’ work 83 Business Systems Research | Vol. 15 No. 1 |2024 Thus, the given approach and the developed means of simulation modelling helped predict the results of managerial influences on specific activities of business processes requiring optimisation. The simulation experiments for both business processes were determined as optimal by using the average percentage deviation of the resulting indicators of the built models as a criterion of optimality. These experiments were selected based on their ability to minimise the chosen criterion. The obtained results are shown in Table 6. Table 6 Results of simulation experiments on business process management A1.2 “Lead generation” and A3.1 “Pre-sale” Activity designation Activity characteristics The purpose of simulating management effects An experiment with the best results Predictive value of a variable e(t), % The average growth rate of the resulting indicators, % Conclusion about the results of the experiment А3.1.37 the lowest satisfaction level with the result (60%) To increase the efficiency of the activity due to the financial stimulation of the performer Еxp(3.1)-3 g(A3.1.37) ↑ on 15% 72.6 5.55 The goal has been achieved P11 the lowest satisfaction level with the result (60%) Exp(A12)-1 g(P11) ↑ on 5% 62.6 -5.89 The goal was achieved under the condition of excessive additional funding А3.1.54 the lowest level of resource availability (40%) To increase the efficiency of the activity by reducing the performing time to increase the performer availability level Еxp(3.1)-4 zp(t)(A3.1.54) ↓ on 5% 73.8 -0.72 The goal has not been achieved Q3 the lowest level of resource availability (60%) Exp(A12)-5 zp(t)(Q3) ↓ on 10% 74.4 -0.13 The goal has not been achieved А3.1.57 the lowest level of resource availability (50%) and low satisfaction with the result (70%) To increase the efficiency of the activity due to the performer's financial stimulation and reduction of the activity performance time to increase the performer availability level Еxp(3.1)-7 g(A3.1.57) ↑ on 15% zp(t)(A3.1.57) ↓ on 5% 76.06 2.88 The goal has been achieved P2 the lowest level of resource availability (40%) and low satisfaction with the result (65%) Exp(A12)-9 g(P2) ↑ on 15% zp(t)(P2) ↓ on 5% 65.37 0.12 The goal was achieved under the condition of excessive additional funding Source: Authors’ work The analysis results of the conducted experiments made it possible to form an optimal subset of management influences for each activity according to its type and the BP optimisation strategy of which it is a part and to build a hexagon to form optimal business process management measures (Figure 10). At the same time, the main emphasis should be placed on improving the strategy of managing financial resources through its optimization and restructuring strategy. It was considered through the prism of optimizing organizational and motivational measures and 84 Business Systems Research | Vol. 15 No. 1 |2024 increasing the general accessibility level of performers to the relevant BPs necessary for effective management. Figure 10 Hexagon formation of the IT service company's optimal business process management measures Source: Authors’ work From the analysis of Table 6 and Figure 10, it can be noted that the simulation experiments, the purpose of which was to reduce the time to perform the activity (A3.1.54 and Q3), did not give positive predictions. That indicates the ineffectiveness of using only moral and psychological encouragement measures to increase the productivity of IT company staff. Predictive evaluations of the solutions proposed for activities P11 and P2 of the business process A1.2 “Lead generation” turned out to be low due to the discrepancy between the growth rates of material incentives and the performer's work, regardless of their position. Predicting the effects on activities A3.1.37 and A3.1.57 gave positive results. The goal of increasing the activity's effectiveness Organisational and motivational activities Organisational and motivational activities Activities that require measures to stimulate the effectiveness of the performer's work Activities that require measures to increase the performer's availability level Activities that require measures to stimulate the effectiveness of the performer's work and to increase their availability level Activities that require measures to increase the performer's availability level А3.1.54 Q3 BP A3.1 Strategy for optimising financial resources management BP A1.2 Optimisation and restructuring strategy 85 Business Systems Research | Vol. 15 No. 1 |2024 was achieved, which indicates the reliability and efficiency of the selected management decisions. Discussion In the work, the organisation is considered a complex hierarchical system. The basis of the model presented in the paper was the assessment of business processes at different levels. This assessment became the basis for building a hierarchical model with a business process structure. The logical sequence of the assessment is followed: activity (separate for the business process) – business process of the operational level – business process of the tactical level – transition to the business process of the strategic level. That confirms the step-by-step nature of business processes and correlates with the work of Goel et al. (2021). The proven interrelationships between business processes made it possible to build a model of the optimisation mechanism of the company's IT management processes. The developed model, represented in Figure 4 by the flow diagram of the BP A3.1 management simulation model with the following assessment of adequacy (Table 5), proved the proposed toolkit for managing the development of complex hierarchical systems to have relatively high accuracy. In particular, the given model allows the operation of the business processes of individual functional blocks of the hierarchical system, which is consistent with the conclusions of other researchers (Webler, 2022). However, this model's advantage is precisely the minimisation of information noise since the feedback is carried out according to the state vector, which considers information about the problem cluster. Such block BP management has an advantage over models (Goel et al., 2021; Lee et al., 2019) when considering critical occurrences associated with the lack of financial resources or critical phenomena in HR management. As confirmed by Figure 10, utilising additional levers on activity, which require measures to stimulate performers' work (A3.1.37 and P11), can reduce the possibility of marketing turbulence. For example, in this case, financial and motivational measures will be optimal, which can include: o A salary increase is the simplest and most effective way of motivation. It is formed by many factors, such as the enterprise size, the origin of the enterprise's capital, the field of activity, specific knowledge and skills availability, certificates, etc. o The social package includes health insurance, payment for mobile phone calls, meals, fitness club membership, travel expenses, discounts on the company's goods and services, etc. o The points accumulation system assigning points to the performer for the period of work in the company for participation in projects and other activities, which are then exchanged for any benefit at their discretion o The incentives through the choice of equipment for work at their discretion at the company's expense, provided that it then becomes the employee's property. Nevertheless, analysing the approach (Ilmudeen, 2022) and considering the model (Figure 10), it is necessary to reduce marketing turbulence, namely for IT service companies, to exert some influence on measures to increase the performer's availability level (A3.1.54 and Q3). Organisational and motivational measures will be optimal, including: o Competent manager - For IT specialists, the leader's professional qualities are of great importance, as is the manager's ability to become an influential motivational factor for employees, especially in the IT industry. The information 86 Business Systems Research | Vol. 15 No. 1 |2024 technology department is a relatively separate unit; it has its own rules, style of communication, clearly expressed specific interests, etc., so the manager needs to understand this o Convenient location of the office, the possibility to work at home is a significant factor in reducing the time to complete the task o Flexible and convenient work schedule - is an important motivating factor for any IT specialist, provides comfort and promotes an individual approach to optimising the employee's working capacity o IT professionals’ team – a way to gain the necessary experience and improve the skills o Freedom in corporate communication – rejection of standards and regular meetings or brainstorming sessions for all in favour of groups or communities in messengers o Distribution of tasks according to the employee's qualifications o Non-financial encouragement of employees (shortened working day, an opportunity to hold a meeting, give a lecture, etc.) o Promoting the development of time management skills, self-motivation and meeting deadlines among employees. Considering the proposed management paradigm in terms of efficiency and business importance, as suggested by Shoukry et al. (2021), in addition to the mentioned author, it is possible to emphasise stimulating labour productivity and increasing the performer's availability level (A3.1.57 and P2). In this case, according to the model (Figure 10) and the conducted simulation experiments, organisational, motivational, and financial measures will be optimal: o Introduction of a changeable bonus component into the salary for projects and non-standard tasks in addition to the mandatory norms o Social package – payment of specialised it training, mobile communication, home internet and computer o Ensuring comfortable conditions at the workplace - the opportunity to have a snack and rest in the office, providing a comfortable microclimate on the premises o Use of effective work tools (appropriate modern software tools). When creating a model to optimise an IT company's business processes, it is essential to consider the representatives of BP groups with an increased and excessive resource management risk. This model can determine the optimal number of performers required to ensure the minimum cost of implementation and the necessary level of performance efficiency for the chosen BP activities. Optimising representative processes led to a 3.26% increase in the company's entire BPMS efficiency, which was determined using the econometric models for assessing BP's effectiveness. The obtained simulation calculations were confirmed in practice in a Ukrainian IT service company AltexSoft. For the formed BP groups and the structure as a whole, an efficiency indicator was assessed based on the results of building econometric models, which showed an average increase in BP efficiency by 6%. The advantages of the BP's newly formed functional structure are: o The implementation of a close connection between the BP of the highest management level and the BP that implements functional management o Increasing the importance of functional managers o Reducing the need for performers of a comprehensive profile o Decreasing the time between decision-making and implementation o Reducing intermediate links between the manager and the performer solutions 87 Business Systems Research | Vol. 15 No. 1 |2024 o Lowering the effectiveness dependence of some processes on others due to forming groups united by the type of performed functions. Conclusions The work proposed a general algorithm for building and analysing business process optimisation models of the IT company. The study identified groups of business processes that had a significant decrease in the level of utilization of the company's labour and financial resources. Also, these BPs were characterised by a high level of management risk, which had an impact on the management of the company. An IT company's business process management was analysed and optimised using simulation modelling and scenario modelling. That included a predictive assessment of management impacts on business processes to identify the most effective solutions for specific activities within individual clusters based on defined management strategies. The BP's management strategy and specific activity were considered while developing the optimal business process management measures for a service IT company. Based on the obtained results, a hexagon was formulated. It provides a set of measures to choose from, including financial and motivational, organisational, and motivational, or organisational, motivational and financial measures. The results obtained in the study became the basis for the formation of an optimal pool of management influences, considering the type and strategy of BP optimisation for each activity. The limitation of the presented study is the use of average model values for the simulation period. That relatively generalises the obtained result but simultaneously allows the presentation of the situation in terms of basic processes in relation to any IT company. Thus, the article offers a significant scientific contribution by presenting a comprehensive model that IT companies can utilise to introduce and optimise various BPs. Consequently, critical processes in developing complex hierarchical systems, which arise due to the systemic inconsistency of individual BPs or result from synergistic effects during the optimisation of other BPs, can be promising research on the specified topic. References 1. Biddle, J. E. (2020). 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Webler, F. (2022). Measurement in the age of information. Information, 13(3), 111. https://doi.org/10.3390/info13030111 28. Xing, L., Levitin, G., & Wang, C. (2019). Dynamic system reliability: Modelling and analysis of dynamic and dependent behaviors. Hoboken, United States: John Wiley & Sons Ltd. https://doi.org/10.1002/9781119507642 90 Business Systems Research | Vol. 15 No. 1 |2024 About the authors Olena Serhiienko, Ph.D., is a Professor at the Department of Business, Trade and Logistics, National Technical University "Kharkiv Polytechnic Institute". Her research interests are the development and modelling of complex hierarchical systems (CIS), management of trading enterprises based on intellectual information systems, implementation of the marketing policy of a trading enterprise, and information and analytical support for making management decisions in business. The author can be contacted at [email protected] Maryna Mashchenko, Ph. D., is a Professor and head of the Department of Business, Trade and Logistics at the National Technical University Kharkiv Polytechnic Institute. Her research interests are the environmental security of industrial enterprises and the management of entrepreneurial strategies in innovative businesses. The author can be contacted at Mashch[email protected] Borys Samorodov, Ph.D., is a Full Professor at the Department of Banking Business and Financial Technologies, Education and Research Institute Karazin Banking Institute, V.N.Karazin Kharkiv National University. His research interests are in the following areas: optimisation technologies in finance and banking, the use of rating technologies for the diagnosis of financial and socioeconomic systems, the use of mathematical and information technologies for solving economic problems, and the financial stability of the banking sector in the region. The author can be contacted [email protected] Anatoliy Babichev, PhD, is a Vice-Rector for Academic Affairs and Associate Professor of the Department of Management and Administration of Karazin School of Business, V.N.Karazin Kharkiv National University. He has 5 years of scientific and teaching experience at V. N. Karazin Kharkiv National University. His research interests include public management and administration, higher education management, business communications and presentation skills. The author can be contacted at [email protected] Olena Klimenko, Ph.D., is an Associate Professor at the Department of Public Administration, Public Administration and Economic Policy, Simon Kuznets Kharkiv National University of Economics. Her research interests include economic development and problems of economic regulation, forecasting and modelling in the context of accelerated European integration: digitisation, cyclical policy, environmental economics, innovation and investment policy of the state in times of crisis, socio-economic problems and improving the quality and standard of living of the population. The author can be contacted at [email protected]