Numeric measurement of business process optimization

Cite as: Miroshnychenko I., and Bradul, O. (2023). The influence of corporate management on the optimization of business processes. Economic analysis, 33 (4), 253-260. DOI: https://doi.org/10.35774/econa2023.04.253 The relevance of the study is due to the fact that today the economic situation in Ukraine in connection with the military aggression of a neighboring country has acquired a rather critical state, as a result of which many domestic corporations are losing production ties, key suppliers and sales markets, reducing business performance indicators processes. Therefore, the main task of corporate management is to find ways to optimize business processes in the existing conditions and direct all the potential of the corporation to maintain and preserve the business. The purpose of the study is to determine the specifics of the impact of corporate governance on the optimization of the enterprise's business processes. The object of the research is cooperative management and its influence on the optimization of the corporation's business processes. The theoretical analysis within the scope of this study was carried out on the basis of the methods of analysis, systematization, generalization and comparison of the theoretical provisions of various researchers regarding the definition of the essence and content of corporate management, as well as its influence on the optimization of the enterprise's business processes. Based on the results of a critical review of scientific works on the essence of corporate governance, the following scientific approaches to its interpretation were distinguished: classical, managerial, regulatory, controlling, strategic, effective, shareholder stakeholder. The author's vision of a complex system of interaction of such approaches based on their systematization into three groups (interest, management, effect) is proposed. At the same time, interest-group approaches are distinguished by a greater attention of scientists to the issues of satisfying the interests of participants in corporate relations, management - an emphasis on management functions and tasks of corporate management, and the effect - on obtaining the desired results from such management in a strategic perspective. The definition of corporate governance is proposed as a system of managing corporate relations in an organization that functions in order to realize its strategic goals by ensuring the effectiveness of the mechanism for making effective decisions based on the regulation and control of corporate rights and monitoring the results of activities to ensure the balance of interests of participants in corporate relations. The content of the concept of "optimization of business processes" in the environment of corporate management is proposed, which is based on the key role of corporate management, which develops a strategy aimed at the result.

This work considers the optimization and development of business processes in investment. The conditions for the digitalization of the economy actualize the issue of introducing information technologies at all its levels and links. It is proved that information technology is an effective tool for reducing the time for the implementation of individual business processes and in investment. Its use expands the possibilities of exchanging information and its dissemination to the general public, improves the quality of investment tasks and the objectivity of investment decision-making results. Experimental studies have confirmed that the result of its application is the efficiency of obtaining, processing, and analyzing information when making management decisions. The visual content of the results of investment analysis, obtained using automation technologies, facilitates the perception of information, improves the quality of its transmission, and the value of ideas. The continuous development of information technologies in the field of investment is the basis for further scientific and practical research in this area. Based on such considerations, the feasibility of modifying the methodical toolkit of financial calculations in the process of analyzing the effectiveness of investment implementation is justified. Models of the modified internal rate of return on investment and the rate of return on financial management are proposed. Based on their definition, the objectivity of evaluating investments increases, the effectiveness of cash flow management during their implementation is proved. Strengthening the manifestation of crisis phenomena actualize the study of the nature of the occurrence of risks and the degree of their controllability. The approach to assessing investment risks using the β coefficient, the calculation technology, which is a universal tool for assessing the impact of systemic risks at the macro and micro levels, is substantiated.

This article discusses the problems of introducing an effective business, as well as optimizing business processes. Various approaches to managing and optimizing business processes are analyzed. The reasons for which it is necessary to improve the process and each component of this process are identified and described. Two main approaches to improving business processes are considered: functional and approach, the main differences between them, as well as the advantages and disadvantages of each of them are demonstrated. Any process has a life cycle, thanks to which it follows the article considers the life cycle of six sigma. Based on the material studied, methods for improving business processes are proposed, and the role of the leader is examined, and concepts such as creative management and a creative manager are examined and what their role is in modern business. Any life cycle needs modeling, timely improvement, so that the company can get good results, so managers and chief managers must follow the simple rules discussed in the article in order to simulate the business process as is and as it should be , you can use the Business Process Management Notation and special software designed for this. The general conclusion of the article is that each company should choose its own approach and method of optimizing business processes based on general principles. Key words: business processes, processes, process management, optimization.

The article explores the vital subject of optimizing business process management, which is essential for enhancing the efficiency and competitiveness of enterprises. The study evaluates various perspectives, including economic, engineering, and managerial aspects, and underscores the importance of mathematical models over descriptive models in achieving precise and effective optimization. Descriptive models, despite their widespread use, do not guarantee optimal outcomes. The article emphasizes the need for mathematical models to accurately optimize business processes, considering various criteria and constraints. This approach aims to address the limitations of current descriptive models and advocates for the development of specific mathematical models to manage business process optimization under uncertainty. Key findings reveal that optimization in business process management has a significant impact on enterprise efficiency, productivity, and competitiveness. The process approach, which concentrates on enhancing individual business processes, is highlighted as a crucial paradigm in modern management. The research calls for further investigations to develop mathematical models that can deliver more reliable and precise optimization results, especially in uncertain conditions. In conclusion, the article supports the transition from descriptive to mathematical models in optimizing business process management to achieve maximum efficiency and competitiveness in enterprises. Future research will focus on developing mathematical optimization models for business processes, particularly those related to new product development under uncertain conditions. This shift is anticipated to offer more accurate and effective solutions for optimizing business processes in a dynamic and unpredictable business environment. Furthermore, the article highlights the need for continuous development and application of mathematical approaches to ensure that business processes are optimized effectively. It stresses the importance of incorporating various optimization criteria and constraints to achieve the best possible outcomes. By transitioning to mathematical models, businesses can better navigate the complexities and uncertainties inherent in today's competitive landscape, leading to improved performance and sustainable growth.

This paper describes a method for the implementation and optimization of business processes in a service oriented architecture (SOA). A process specification is created by business people, and expressed in Business Process Modeling Notation (BPMN). The specification is then translated into Business Process Execution Language (BPEL), and used by technical people as a reference process, which is subject to a series of transformations that change the internal process structure in order to improve the quality of the process execution. The behavior of each transformed process is verified automatically against the behavior of the reference process. The verification mechanism is based on a mapping from BPEL to Language of Temporal Ordering Specification (LOTOS), followed by a comparison of the trace set that is generated using a program dependence graph of the reference process and the trace set of the transformed one. When the design goals have been reached, the transformed BPEL process can be executed on a target SOA environment using a BPEL engine.

Business process's performance determine the whole enterprise's economic profit, researching work on business process's optimization is very useful and meaningful. This thesis point out that manager must take the dynamic environment and multiple objectives into account while optimizing the enterprise's business process. Based on the theory of multiple objective optimizations, AHP, and simulation technology, the thesis builds a dynamic simulation model for business process optimization. Firstly the basic concept of business process is introduced. Secondly the framework of simulation model is put forward, the framework include logic of the simulation process and parameters' selection. Thirdly, the thesis researched the business process' s performance evaluation method, and proposed a review model based on AHP, point out that there is a balanced point among time, cost and quality, and the point can help us to find the optimal design of business process. Finally, the thesis provide a experiment to verify the validity of the model put forward by the thesis, and the result prove that the model is effective in optimization of business process.

The article is devoted to the topical issues of artificial intelligence (AI) technology for managing the optimization of business processes under the influence of changing SEO trends in 2025, which is important and requires the identification of the main vectors of their further development for implementation in the work of the business. In the modern world, where information has a dynamic development and becomes a digital asset, the use of AI plays a significant role for managers and clients, which determines the development of the functional intelligence of the future management network. The research consists of analyzing the main approaches in the context of business process management regarding their optimization in the field of security, taking into account the changing trends of SEO in 2025 using AI, which will contribute to increasing the efficiency of business decisions. The main trends of AI influence on the development of SEO optimization in website promotion in 2025, which has a positive impact on business development and the effectiveness of indicators, are summarized. The vectors of management efficiency through the impact of AI technology on the optimization of business processes in the field of security services, which will contribute to timely response to the challenges and risks of the modern competitive environment, are determined. In conclusion, it is emphasized that for improving the management of business processes regarding their optimization, it is necessary to use AI, in particular in the field of security, taking into account SEO trends in 2025, through the analysis of current processes, identifying priority goals of business process optimization, improving existing processes and developing new ones taking into account the use of modern technologies and monitoring business results by implementing changes in order to adjust them. These vectors contribute to the optimization of business processes in the field of security, but there is a need to take into account the cost of AI implementation and training of security guards who have to work with AI technology and understand how to interpret the data obtained. An important challenge is the solution of an ethical issue that concerns the confidentiality and protection of personal data of clients. It has been found that AI has significant potential for optimizing business processes in the field of security regarding increasing management efficiency, improving the quality of service, which will lead to business performance. The vector of further research lies in the wide application of AI in management, which will bring the business to a qualitatively new level of management, defining the development of the functional intelligence of the future management network.

In a competitive environment, enterprises success depends on the effectiveness of their business processes, which leads to the search of a continuous improvement in the time. This kind of improvement is called business process optimization. Yet, two major challenges often prevent processes optimization. First, the skills of the analysts to choose the right process among a number of propositions. Second, the techniques applied to generate and evaluate solutions during optimization process are poor and do not include all relevant data. Our Evolutionary Business Process Optimization approach addresses these challenges through a well-defined mathematical representation and a novel evolutionary algorithm as optimization facilities. In this paper, we focus to use of a formalized process optimization approach for generating and improving business process designs.

Significant opportunities for improvement exist in the optimisation of business processes. The use of statistically-based methods to characterise business process performance is one way to realise those improvements. Business processes can be difficult to characterise due to variables that are difficult to define, measure and analyse. Outputs in the business process may be qualitative or binary in nature. The cause and effect relationships among inputs, actions and outputs may be difficult to observe and monitor. Sources of variation exist throughout the process, but may be difficult to identify and control. Consequently, statistically-based characterisation methods that have been proven successful for manufacturing processes may not be directly applicable to business processes. Because many of the variables in these business processes are subjective or qualitative in nature, categorical data analysis techniques may be useful. This paper illustrates the use of logistic regression to establish statistically significant relationships between the input and output variables of one complex business process.

Generally, the environment and enterprises' condition are not stable, in order to promote the enterprises' competitive power, mangers must continuously improve the business processes' performance. Based on the simulation method and multi-objective optimization theory, the thesis builds a dynamic multi-objective optimization model for business process optimization. Firstly the framework of optimization model is introduced, the framework include logic of the simulation process and parameters' selection. Secondly, a business process's performance review model is given for evaluation, and also point out that there is a balanced point among time, cost and quality, and the point can help us to find the optimal design of business process. Finally, the thesis provide a experiment to verify the validity of the model put forward by the thesis, and the result prove that the model is effective in optimization of business process.

This research focuses on operator positioning using inspection trajectory data from Liaohe Oilfield's production sites, with emphasis on the Beidou + Bluetooth + UWB technical route implemented in the 2024 pilot project. It analyzes drawbacks of traditional manual positioning methods: poor data accuracy, insufficient real-time performance, and high susceptibility to environmental interference. The study demonstrates that Beidou positioning achieves meter-level accuracy (1-5m) in outdoor environments with strong anti-interference capability, while Bluetooth enables reliable indoor positioning with sub-meter to meter-level accuracy (2-3m) and low power consumption, and UWB provides centimeter-level precision for high-risk safety-critical scenarios. Field validation shows the integrated Beidou+Bluetooth system achieves full-scenario coverage from outdoor open areas to indoor workshops. A four-level management model ("Positioning Technology Integration - Business Process Optimization - Data Mining & Analysis - Intelligent System Response") enables dynamic route optimization and real-time anomaly warnings. The pilot application results confirm efficiency improvement over 30% and missed inspection rate reduction by 25%, providing a practical paradigm for intelligent safety management in oil and gas fields.

One of the key issues in corporate management is business process management. That is why the greatest interest for company analysts is the issue of effective forecasting of business processes. In today's digitalization of the economy, integration and automation of business processes have become the main priorities for achieving efficiency and effectiveness of companies, and especially for effective management decisions. This problem can be solved with the help of integrated systems, which are tools for effective management decisions, modeling and optimization of business processes. The article provides an analytical review of known forecasting methods and identifies the features of their application, analyzes the advantages and disadvantages that will take them into account in modeling the company and promote economic development, competitiveness and optimize business processes.

Models of artificial intelligence integration into business processes (‘AI as a tool’, ‘AI as a partner’, ‘AI as a driver’) have been studied. It has been proven that artificial intelligence is not only a tool for automation, but also a driver of digital transformation, providing new decision-making logic, business process optimisation and personalisation of the customer experience. Cases of AI integration into the business processes of leading companies (Amazon, Coca Cola, Siemens, Netflix, Unilever, Microsoft) were analysed, and global practices were analysed that indicate a transition from point solutions to systemic transformation. The study revealed a clear trend towards the integration of AI into the intelligent automation of business processes in order to create end-to-end autonomous processes – production, logistics, marketing, etc. Generative artificial intelligence models are used as a tool for creating effective prompts for managing and optimising business processes, automating individual operations such as corporate chatbots, customer segmentation, supply chain optimisation, warehouse robotics management, energy cost savings, etc.

This study examines the correlation between IT application maturity, Business Process Optimization (BPO), and Management Model Innovation (MMI) in the context of enterprise Digital Transformation (DT). Despite widespread DT adoption, organizations often treat BPO and MMI as separate outcomes, limiting strategic coherence. Using a quantitative-dominant mixed-methods approach, data were collected from 362 enterprises across manufacturing, finance, logistics, and healthcare sectors through structured surveys and KPI extractions from ERP/BPM systems. Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) were employed to test hypotheses, with process mining used for validation. Results reveal a strong direct effect of IT maturity on BPO (β = 0.69, p < 0.001) and a moderate direct effect on MMI (β = 0.31, p < 0.001), with BPO partially mediating the relationship (indirect β = 0.28, p < 0.001). Sector-wise, manufacturing and finance showed stronger effects compared to healthcare and logistics. Large enterprises outperformed SMEs, attributed to greater digital capabilities and resources. Process mining confirmed significant post-DT improvements, including 19.7% cycle time reduction and 28.9% error rate reduction. This study offers a validated model linking digital capabilities to process and management innovation, emphasizing the importance of aligning IT adoption with operational excellence and organizational readiness in digital transformation initiatives.

The current business environment has no room for inefficiency as it can cause companies to lose out to their competitors, to lose customer trust, and to experience cost overruns. Business processes within the company continue to grow and cause them to run more complex. The large scale and complexity of business processes pose a challenge in improving the quality of process model because the effectiveness of time and the efficiency of existing resources are the biggest challenges. In the context of optimizing business processes with a process mining approach, most current process models are optimized with a trace clustering approach to explore the model and to perform analysis on the resulting process model. Meanwhile, in the event log data, not only the activities but also the other resources, such as records of employee or staff working time, process service time, and processing costs, are recorded. This article proposes a mechanism alternative to optimize business processes by exploring the resources that occur in the process. The mechanism is carried out in three stages. The first stage is optimizing the job shop scheduling method from the generated event log. Scheduling the time becomes a problem in the job shop. Utilizing the right time can increase the effectiveness of performance in order to reduce costs. Scheduling can be defined as the allocation of multiple jobs in a series of machines, in which each machine only does one job at a time. In general, scheduling becomes a problem when sequencing the operations and allocating them into specific time slots without prolonging the technical and capacity constraints. The second stage is generating the resource value that is recorded in the event log from the results of analysis of the previous stage, namely, job shop scheduling. The resource values are multivariate and then clustered to determine homogeneous clusters. The last stage is optimizing the nonlinear multipolynomials in the homogeneous cluster formed by using the Hessian solution. The results obtained are analyzed to get recommendations on business processes that are appropriate for the company’s needs. The impact of long waiting times will increase service costs, but by improving workload, costs can be reduced. The process model and the value of service costs resulting from the mechanism in the research can be a reference for process owners in evaluating and improving ongoing processes.