Business Process Automation Research Articles

Robotic Process Automation (RPA) in Business Processes: Benefits and Challenges

Robotic Process Automation (RPA) has emerged as a transformative technology in the realm of business process automation. This research paper investigates the benefits and challenges of implementing RPA in various business processes. The paper provides an overview of RPA, highlighting its key features and capabilities. It then identifies the challenges faced by organizations during RPA adoption and implementation. The research also explores existing RPA systems and analyzes their strengths and limitations. A proposed RPA system is presented, aiming to address the identified challenges and enhance the overall efficiency of business processes. The findings reveal that RPA offers significant advantages in terms of increased productivity, cost savings, and improved accuracy, but it also requires careful planning and management to overcome potential hurdles. This research paper contributes valuable insights into RPA's integration and deployment, enabling organizations to make informed decisions on adopting this transformative technology

A Guide to Wireless Technology and to drive an Industrial revolution using 5G

The mobile wireless communication started from 1G which has the ability to use a phone inside the car, or away from home. 2G was introduced for short-messaging layer. 3G the core network which made available to launch the first smart phones. And 4G LTE, with its high data-transfer rates, gave access to mobile video with low buffering and gave rise to many of the connected devices and location services that we rely on. But in this paper we discuss about 5G technologies. 5G is called as Fifth generation of cellular technology. 5G is a unified, and it is capable of air interface. It is designed to deliver higher multi-Gbps peak data speed, to reduce latency and improve flexibility of wireless communication.5G also enhances digital experiences through machine-learning (ML)- enabled automation. Advancements in virtualization, cloud-based technologies, and IT business process automation enable 5G architecture to be agile and flexible and to provide anytime, anywhere user access. Keywords: IMT, D2D, Cache, EPC, RAN

Design of Data Warehouse Technology for Data Performance Management in Universities

The purpose of this research is Change Management for Organizations to find out change management for organizations and organizational change factors by using the nine steps methodology approach developed by Kimball. The results of this study are that information technology assistance provided by Pelindo I is the right step. Moreover, the scope of the business being managed is so wide, covering ports in the Sumatran archipelago and overseeing thousands of employees. Business process automation is becoming an effective way for companies to force irresistible change. If the rules are written, even though they have been mutually agreed upon, employees can still work around them. But technology can be coercive effectively and can eventually lead to cultural change. Performance management is simply productivity, how can employee productivity be measured based on predetermined targets? MKE Pelindo I with a technology base makes everything completely objective, transparent, and has clear measurements. When each person is competing to make an optimal contribution to the company, at that time all the wheels of the organization will move dynamically. Then based on Kotter's 8-step evaluation, the change process that was carried out for the first time in 2004-2014 which was not conducive was caused by the not forming a strong enough team to direct the process. And this is what creates resistance also from employees. Then it wasn't created at the beginning of creating the right vision, but changes had been implemented, meaning that subordinate employees were invited to change without communicating a vision.

Stairway to heaven or highway to hell: A model for assessing cognitive automation use cases

Cognitive automation (CA) moves beyond rule-based business process automation to target cognitive knowledge and service work. This allows the automation of tasks and processes, for which automation seemed unimaginable a decade ago. To organizations, these CA use cases offer vast opportunities to gain a significant competitive advantage. However, CA imposes novel challenges on organizations’ decisions regarding the automation potential of use cases, resulting in low adoption and high project failure rates. To counteract this, we draw on an action research study with a leading European manufacturing company to develop and test a model for assessing use cases’ amenability to CA. The proposed model comprises four dimensions: cognition, data, relationship, and transparency requirements. The model proposes that a use case is less (more) amenable to CA if these requirements are high (low). To account for the model’s industry-agnostic generalizability, we draw on an internal evaluation within the action research company and three additional external evaluations undertaken by independent project teams in three distinct industries. From a practice perspective, the model will help organizations make more informed decisions in selecting use cases for CA and planning their respective initiatives. From a research perspective, the identified determinants affecting use cases’ amenability to CA will enhance our understanding of CA in particular and artificial intelligence as the driving force behind CA in general.

CORPORATE INFORMATION SYSTEM FOR COMPLEX AUTOMATION OF BUSINESS AND PRODUCTION PROCESSES DURING WELL CONSTRUCTION

The lack of a unified information space and unified approaches to well construction planning leads to inefficient use of the working time of highly qualified specialists, while reducing the efficiency of the process. For the comprehensive automation of business and production processes during the construction of wells, TATNEFT has created a corporate information and analytical system "Drilling". The system is implemented on the domestic platform 1C: Enterprise and allows you to plan the costs and workflows of well construction, as well as control compliance with well construction deadlines and monitor costs. Automation of the process and generation in a single information space on various business processes of well construction increases the availability of information, accuracy of planning, efficiency of decision-making, which, ultimately, will reduce the cost of well construction and increase the efficiency of the process.

Digital technologies: new approaches to the traceability of grain flows in Russia

The article deals with issues related to the development of the grain complex of Russia. Grain, as a strategically important agricultural raw material, serves as an indicator of achieving the country's food security. Despite the significant grain harvest collected in 2022, there are certain internal difficulties in the agro-industrial complex that affect the quantitative and qualitative indicators of grain crops: insufficient working capital, lack of qualified specialists, a large number of enterprises, including small and medium-sized enterprises, technological lag, etc. The national platform “Digital Agriculture” accumulates information about all producers, conditions of storage and transportation of agricultural raw materials. Total digitalization allows the introduction of modern technological solutions aimed at automating business processes and ensuring the traceability of the flow of grain crops and seeds at all stages of the food chain from the moment of cultivation to complete processing, import or export abroad using federal state information systems “Zerno”, “Argus-Fito” and the introduced system “Semenovodstvo”.

STATE INDUSTRY POLICY IN THE FIELD OF IMPORT SUBSTITUTION OF INFORMATION PRODUCTS AT AVIATION INDUSTRY ENTERPRISES

In the research article, the authors consider the main proposals for the implementation of the state sectoral policy in the field of import substitution of information technologies and systems (ITiS) at high-tech enterprises in the aircraft industry in modern innovative and financial conditions. For this, the main features of aircraft manufacturing enterprises that are part of the United Aircraft Corporation (UAC) were considered from the point of view of automating their typical business processes, where the implementation of the state industry policy in the field of import substitution is supposed to be implemented. The authors carried out an organizational and economic analysis of the Russian ITiS market, as well as formulated the main measures and procedures that should be implemented at high-tech aircraft manufacturing enterprises within the framework of the state sectoral policy in the field of import substitution. The article also considers an example of the implementation of the Russian information system in the development of a project for the automation of production accounting at the head enterprise of the UAC as part of the implementation of this policy.
 Purpose – determination of methods and techniques for automating typical business processes of aircraft manufacturing enterprises through the use of domestic information technologies and systems as part of the implementation of the state industry policy in the field of import substitution of information and communication technologies.
 Methodology. The article used methods of empirical research, information-logical and expert methods, as well as methods of analogy and comparison.
 Results. The most informative parameters were obtained, showing the economic feasibility and effectiveness of the introduction of domestic information technologies and systems at aircraft manufacturing enterprises as part of the implementation of the state sectoral policy in the field of import substitution of information and communication technologies.
 Practical implications. The obtained results should be applied not only at the enterprises of the UAC aircraft industry, but also at the enterprises of other high-tech industries of the State Corporation Rostec, where automation of the main standard business processes is an important component of their further development.

DEVELOPMENT UNIFIED APPROACH TO AUTOMATION DOCUMENT TEMPLATE VERIFICATION PROCESS CREATED IN FASTREPORT

The article discusses the business processes automation for creating, modifying and checking templates for printing payment documents in the «FastReport» program using the example of organizations engaged in printing activities. The purpose of the article is to develop software that allows you to automatically check the print template file for all key parameters using information from its own database. The article is recommended to specialists whose work is related to the creation of documents in «FastReport».

The composite approach as a hybrid approach to business process modeling: proposition and empirical evaluation

PurposeBusiness process modeling faces a difficult balance: on the one hand, organizations seek to enact, control and automate business processes through formal structures (procedures and rules). On the other hand, organizations also seek to embrace flexibility, change, innovation, value orientation, and dynamic capabilities, which require informal structures (unique user experiences). Addressing this difficulty, the authors propose the composite approach, which integrates formal and informal process structures. The composite approach adopts a socio-material conceptual lens, where both material and human agencies are supported.Design/methodology/approachThe study follows a design science research methodology. An innovative artifact – the composite approach – is introduced. The composite approach is evaluated in an empirical experiment.FindingsThe experimental results show that the composite approach improves model understandability and situation understandability.Research limitations/implicationsThis research explores the challenges and opportunities brought by adopting a socio-material conceptual lens to represent business processes.Originality/valueThe study contributes an innovative hybrid approach for modeling business processes, articulating coordination and contextual knowledge. The proposed approach can be used to improve model understandability and situation understandability. The study also extends the socio-material conceptual lens over process modeling with a theoretical framework integrating coordination and contextual knowledge.

How automation helps to manage an enterprise with a staff of 10 thousand people

In recent years, many services have appeared that allow you to "digitize" routine, and the forced transfer of employees to remote work due to the pandemic has become a catalyst for automating business processes. However, in practice, this trend is not developing as fast as one might assume: studies show that every second company in Russia still uses Excel spreadsheets for workflow management. Automation is especially difficult to perceive in manufacturing companies, but there are exceptions. The article analyzes how automation helps to manage an enterprise with a staff of 10 thousand people

Dynamic Pricing with Volume Discounts in Online Settings

According to the main international reports, more pervasive industrial and business-process automation, thanks to machine learning and advanced analytic tools, will unlock more than 14 trillion USD worldwide annually by 2030. In the specific case of pricing problems, which constitute the class of problems we investigate in this paper, the estimated unlocked value will be about 0.5 trillion USD per year. In particular, this paper focuses on pricing in e-commerce when the objective function is profit maximization and only transaction data are available. This setting is one of the most common in real-world applications. Our work aims to find a pricing strategy that allows defining optimal prices at different volume thresholds to serve different classes of users. Furthermore, we face the major challenge, common in real-world settings, of dealing with limited data available. We design a two-phase online learning algorithm, namely PVD-B, capable of exploiting the data incrementally in an online fashion. The algorithm first estimates the demand curve and retrieves the optimal average price, and subsequently it offers discounts to differentiate the prices for each volume threshold. We ran a real-world 4-month-long A/B testing experiment in collaboration with an Italian e-commerce company, in which our algorithm PVD-B - corresponding to A configuration - has been compared with human pricing specialists - corresponding to B configuration. At the end of the experiment, our algorithm produced a total turnover of about 300 KEuros, outperforming the B configuration performance by about 55%. The Italian company we collaborated with decided to adopt our algorithm for more than 1,200 products since January 2022.

Web-Based Motorcycle Loan Management System with credit risk and approval analysis using Data Mining Techniques

Using information systems can dramatically improve a business's productivity and efficiency. Moreover, the ability of information systems to provide users with the information they need to complete jobs effectively can be the most significant advantage. This project development plan proposes a Web-Based Motorcycle Loan Management System with credit risk and approval analysis using Data Mining Techniques for a private motorcycle dealer who encounters challenges, particularly in the decision-making of motorcycle loans. It will facilitate the automation of business processes, including online motorcycle loan applications and payments, access to real-time data and reporting, and credit risk and approval analysis to assist the credit department in decision- making by applying data mining techniques. The project will employ the Scrum framework for software development and testing method. A total of 150.625 man-days with a total cost of P1,350,231.78 were computed to complete the proposed information system. A one-year financial viability analysis was defined to determine the proposed project's total cost and benefits. Based on the results, time spent on activities is reduced to 89.19%, indicating that the business can handle more applications every day compared to the average twenty daily applications since processing time is significantly decreased. It is recommended for future improvement of this plan to implement Augmented Reality for a better user online experience in previewing motorcycle units.

Theoretical approaches to digital transformation in enterprise management

The paper is devoted to the study of digital transformation in management. Currently, the problems of implementing an effective digital transformation at enterprises are becoming particularly relevant in the context of the fact that the transformation is one of the key factors in increasing the competitiveness of the organization. Due to the continuous development of technology and the growth of the digital economy, organizations are facing significant changes in the business environment. Digital transformation allows companies to adapt to these changes and use new opportunities to improve efficiency and productivity. The paper examines the definition of digitalization, explores the theoretical foundations of digital transformation in management; due to the significance of the transformation of the organization as the main factor in increasing competitiveness. Digital transformation in today's business environment has become a must for companies seeking to innovate and achieve competitive advantage. Due to the rapid development of technologies, management processes and methods are undergoing significant changes. Digital solutions allow you to automate business processes, simplify data collection and analysis, improve communication and collaboration between different departments and employees. This helps reduce routine work, increase productivity and focus on strategic planning and innovation. However, digital transformation also creates new challenges for management that require attention and solutions. The rapid development of the digital economy, the excessive level of changes in the external environment and market competition require enterprises to optimize and effectively build business processes, as well as focus on improving the competitive strategy.

Directions of application of artificial intelligence in digital marketing communications

The digital transformation of modern economic life has found its reflection in the field of marketing communications, having formed a virtually new form of communication between market entities-digital. A distinctive feature of this form is the personalization of the message, the high selectivity of the consumer’s choice, as well as the possibility of a permanent communication process in which the consumer has the opportunity to independently create content about the company and its product, as well as actively distribute it for their own purposes, sometimes different from the goals of the company. The use of digital marketing communications in the activities of companies provides a number of advantages, such as the infinity and global coverage of the market, the versatility of market impact effects, personalization of communications, etc., which cannot be realized without artificial intelligence technologies. The scope of artificial intelligence in modern companies is extensive. Today, many innovative solutions for the automation of production and other business processes of companies are unthinkable without artificial intelligence. Artificial intelligence is «busy» in routine marketing processes, for example, accompanying the process of purchasing and delivering goods to the consumer, etc. The subject of research in this article is the possibility of creating content, implementing the targeting process and other areas of application in digital marketing communications of artificial intelligence. The object of the study is modern developments in the field of digital marketing communications, which contribute to the formation of effective interactions with the consumer by «fixing» them in behavioral models.

Vehicle Detection Using YOLOv5

Object detection is a computer vision method that allows for the identification and localization of specific classes of objects in images or videos. It goes beyond simple object classification and helps provide a better understanding of the object in question. Object detection has numerous applications, including automating business processes like inventory management in retail. It can detect objects that occupy between 2% and 60% of an image's area and clusters of objects as a single entity. Additionally, it can localize objects at high speeds, typically greater than 15 frames per second. Vehicle detection is a crucial component in the development of autonomous vehicles, enabling them to identify and perceive objects in their environment. It involves identifying and locating vehicles in image or video frames and has various applications in surveillance and security systems. There are different techniques and models for object detection, including traditional image processing methods and modern deep learning networks. Traditional methods like Viola- Jones, SIFT, and histogram of oriented gradients do not require historical data for training and are unsupervised. Popular image processing tools like OpenCV can be used for these techniques. On the other hand, modern deep learning networks like CNN, RCNN, YOLO, ResNet, RetinaNet, and MANet are supervised and efficient for object detection.

Blockchain-Based Business Process Management (BPM) for Finance: The Case of Credit and Claim Requests

Because of the competitive economy, organizations today seek to rationalize, innovate, and adapt to changing environments and circumstances as part of business process improvement efforts. The strength of blockchain technology lies in its usage as an apt technology to enhance the efficiency and effectiveness of business processes; furthermore, it prevents the use of erroneous or obsolete data and allows sharing of confidential data securely. The use of superior technology in the execution and automation of business processes brings opportunities to rethink the specific process itself as well. Business processes modeling and verification are essential to control and assure organizational evolution, therefore, the aim of this paper is three-fold: firstly, to provide business process management patterns in finance, based on blockchain, specifically for the loan-application process in the banking industry and claim process in the insurance industry that could be used and customized by companies; secondly, to critically analyze challenges and opportunities from the introduction of such approach for companies, and thirdly, to outline how companies can implement the loan business process as a web service. Partner companies (a bank and an insurance company) formulated the potential requirements for M2P along with the application of blockchain technology. An experimental design framework was established that gave the necessary services to model the requirements, check the models, and operationalize the models. The applied research methodologies are as follows: design science research paradigm and software case study, model-to-programming (M2P) of business processes, and utilization of patterns of workflow and blockchain.

FEATURES OF THE USE OF ARTIFICIAL NEURAL NETWORKS IN DIGITAL MARKETING

This article examines the possibilities and advantages of using artificial neural networks in digital marketing, describes different types of neural networks. It was determined that neural networks are complex structures created from artificial neurons that can accept multiple inputs to obtain a single output. Artificial neural networks are a subsystem of machine learning, which in turn is a subsystem of artificial intelligence. In the processes of creating content for “sales funnels” and optimizing it to generate quality traffic, neural networks have long proven themselves as a worthy replacement for traditional approaches. Considerable attention in this study is focused on studying the possibilities of using neural networks for data analysis, forecasting trends and solving marketing analytics problems. The main types of artificial neural networks that are currently used in marketing activities are systematized and classified. Key functions that can be performed by neural networks in the context of digital marketing are highlighted, such as forecasting the demand for goods and services, researching consumer behavior, analyzing the competitive situation on the market, recommendations for managing product portfolios, automating business processes, etc. It is emphasized that marketers and managers can use neural networks to improve three strategic areas: segmentation, targeting and positioning.It is noted that attempts to systematize knowledge about artificial intelligence and machine learning in marketing provided the formation of theoretical foundations for the development of consumer-oriented applications in the context of consumer experience and personalized communications. Despite the significant number of advantages of using artificial neural networks in digital marketing, there are also a number of disadvantages and threats associated with artificial intelligence technologies. The use of neural networks is an effective and promising tool in digital marketing, but it requires significant technical and financial costs, and also raises ethical issues that must be resolved before using neural networks for marketing purposes. Further research in this direction can help companies achieve more effective results in their digital marketing strategy.

Computer Vision Application Analysis based on Object Detection

Object detection is a computer vision method that allows for the identification and localization of specific classes of objects in images or videos. It goes beyond simple object classification and helps provide a better understanding of the object in question. Object detection has numerous applications, including automating business processes like inventory management in retail [1]. It can detect objects that occupy between 2% and 60% of an image's area and clusters of objects as a single entity. Additionally, it can localize objects at high speeds, typically greater than 15 frames per second. Vehicle detection is a crucial component in the development of autonomous vehicles, enabling them to identify and perceive objects in their environment. It involves identifying and locating vehicles in image or video frames and has various applications in surveillance and security systems. There are different techniques and models for object detection, including traditional image processing methods and modern deep learning networks. Traditional methods like Viola-Jones, SIFT, and histogram of oriented gradients do not require historical data for training and are unsupervised. Popular image processing tools like OpenCV can be used for these techniques. On the other hand, modern deep learning networks like CNN, RCNN, YOLO, ResNet, RetinaNet, and MANet are supervised and efficient for object detection. Key Words: Deep learning, OpenCV, object detection

Оценка уровня критичности операционного риска банка на основе нейросетевых технологий

The article is devoted to the issues of controlling the operational risks of a credit institution arising in the process of using IT technologies. Among banking risks, operational risk occupies a special place, primarily due to the fact, that it affects various areas of banking activity and is difficult to separate from other types of risk. Operational risks arise, among other things, as a result of downtime or incorrect operation of technical systems and equipment. Due to the constant growth in the degree of automation of banking business processes, new IT risk groups are emerging that can have a significant impact on the activities of a credit institution. The aim of the work is to create an artificial neural network using the high-level Keras library in Python, which automatically controls the level of criticality of the IT risk that has arisen. In the article, based on the analysis of risk events associated with the use of IT technologies, the data flows entering the input of the neural network is identified and its structure is determined. The paper also presents the results of training a neural network created by the authors based on the generated data sets. The use of intelligent methods for assessing the level of criticality of operational IT risk allows you to quickly take measures to minimize the consequences, and thus reduce direct and indirect losses. In connection with the above, the automation of operational risk management based on the use of neural network technologies is currently one of the most urgent tasks for credit institutions. The results obtained are new and can be used by credit institutions in the process of building automated systems for monitoring and managing operational risks.

DIGITALIZATION OF ENTERPRISE WITH ENSURING STABILITY AND RELIABILITY

The article is devoted to the development of an information system for automating business processes of a modern enterprise with ensuring stability and reliability, which are implemented by the applications developed by the authors. Goal is to develop improvements to the core digitalization processes of enterprises for sustainable functioning. The authors carried out a deep analysis and described the main stages of the enterprise digitalization process: the process of document approval, business processes of personnel management, etc. The architecture of the information system, a description of business processes and the principles of reliability and fault tolerance of the system being developed have been developed. The developed desktop-client application provides connection to the information system with the help of working computers of the enterprise through a local network with access to the application server. This allows you to reduce damage from accidental or deliberate incorrect actions of users and administrators; separation of protection; a variety of means of protection; simplicity and manageability of the information system and its security system.