Machine Learning for Smart Inventory Replenishment in ERP Systems

Demand forecasting is a critical function in Enterprise Resource Planning (ERP) systems, directly influencing inventory management, production planning, and overall operational efficiency. Traditional statistical models often fall short in handling the complexity and variability of modern supply chains. This study investigates the application of Artificial Intelligence (AI), specifically Machine Learning (ML) algorithms, to enhance demand forecasting accuracy within ERP environments. I conduct a comparative analysis of four widely used ML models: Linear Regression, Random Forest, Support Vector Regression (SVR), and Long Short-Term Memory (LSTM) networks. Using real-world ERP datasets, each model is evaluated based on Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and computational performance. The results reveal that while Random Forest and LSTM models outperform others in terms of accuracy, their complexity and training time vary significantly. My findings highlight the trade-offs between model accuracy and computational efficiency, offering practical insights for ERP stakeholders. This study contributes to the growing field of AI-driven enterprise analytics and provides guidance on selecting appropriate ML techniques tailored to specific forecasting needs within ERP systems.

Every business or government agency needs to track information regarding their finances, their employees, and the items or assets they own and manage. Software applications that track this type of information are called enterprise resource planning (ERP) systems. Managing these assets in an integrated application allows an organization to have a consistent view across the entire enterprise. This enterprise-wide view allows ERP systems to go beyond the traditional transaction-based accounting systems maintained at the organization level and deliver fully integrated financial and human capital management based on industry-derived best practices across organizations. In response to the pressures of global competition, enterprises today are forging ahead with the mission of integrating information systems across corporate boundaries to unite customers, suppliers and any other business partners with which they interact. And in the mean time, with the development of the society, more and more people have to go many places because the job makes them and working at home also becomes more and more popular. Those people who are not at the place of their company also want to continue their work in other places even at home. The old style ERP system is in C/S model and cannot satisfy with the needs. So it is very necessary to upgrade the ERP system. This paper will go to figure out the application of the Web service in the upgrading of ERP system. In this paper, we focus on that how to upgrade or renew a C/S ERP system to an ERP system with B/S model and the application of Web service. We use the J2EE architecture and XML technology to provide Web service and upgrade/renew the former ERP system. UML tools play a very important role in the upgrading procedure. We use UML to analysis and design the B/S ERP system, which based on the C/S version. We use JSP to act as the view of the system because of its flexibility. In the Web service, the XML is necessary. So the XML technology is also used. In the end of the paper, we will figure out how these technologies to be used through a concrete example.

Enterprise Resource Planning (ERP) systems have emerged as essential tools in streamlining financial reporting and improving management efficiency across various industries, including large-scale energy operations. This theoretical review explores how ERP systems enhance financial reporting by integrating real-time data, automating financial processes, and fostering transparency. In energy operations, where financial activities are complex and data-intensive, ERP systems centralize financial data, reducing errors, improving compliance, and supporting decision-making through enhanced visibility and accuracy. By automating tasks such as budgeting, forecasting, and financial statement generation, ERP systems enable energy companies to efficiently manage their financial resources, thus optimizing cost control and profitability. Additionally, ERP systems provide significant benefits for management efficiency, particularly in large-scale operations. The integration of financial, operational, and managerial processes within a single platform allows for better resource allocation, improved communication across departments, and faster response times to market fluctuations. These capabilities are crucial in the energy sector, where companies face volatile market conditions, regulatory pressures, and high operational risks. ERP systems enhance managerial decision-making by providing real-time insights into key performance indicators (KPIs), enabling executives to make data-driven decisions that support long-term strategic goals. However, implementing ERP systems in large-scale energy operations presents challenges, including high costs, lengthy implementation periods, and the need for employee training. This review also examines these barriers and suggests strategies for successful ERP adoption, including phased implementation, stakeholder engagement, and customization to industry-specific needs. In conclusion, ERP systems hold the potential to revolutionize financial reporting and management efficiency in large-scale energy operations. By leveraging ERP's real-time data integration and process automation, energy companies can significantly improve their financial management, enhance decision-making, and adapt more quickly to market changes. Keywords: ERP Systems, Financial Reporting, Management Efficiency, Large-Scale Energy Operations, Process Automation, Real-Time Data Integration, Decision-Making, Cost Control, Market Fluctuations, Energy Sector.

The emergence of the Internet of Things (IoT) has revolutionized companies by facilitating real-time data collecting, processing, and decision-making among networked devices. Traditional Enterprise Resource Planning (ERP) systems have difficulties in assimilating extensive, varied, and rapid IoT data streams, leading to inefficiencies in decision-making, resource management, and operational performance. This article delineates critical obstacles, such as data synchronization, scalability, and security, that hinder the smooth integration of IoT with ERP systems. This paper offer a complete architecture for the integration of IoT-enabled real-time data into ERP systems to tackle these difficulties. The framework utilizes sophisticated middleware solutions, machine learning techniques, and edge computing to provide efficient data processing, synchronization, and actionable insights. Real-time dashboards and analytical tools are designed to improve user engagement and support informed decision-making. The suggested methodology was assessed using a real-world IoT-enabled ERP dataset, resulting in notable enhancements in predictive accuracy and operational analytics. Machine learning models like XGBoost had exceptional performance, attaining an accuracy of 98.51%, precision of 98.69%, and excellent recall and F1-score metrics. These outcomes underscore the framework's capacity to convert ERP systems into dynamic, adaptable platforms that meet contemporary corporate requirements. Future endeavors will concentrate on resolving interoperability, scalability, and data security issues to optimize the advantages of IoT-ERP integration for enterprises.

ERP (Enterprise Resource Planning) system is considered to provide benefits for the company. ERP systems provide useful accounting information for decision making. This
\nstudy aims to determine the impact of ERP systems on the relevance of accounting information and firm performance on companies that adopt ERP and companies that do not adopt ERP. In this study the relevance of accounting information is tested with three variables of predictive value, timeliness and feedback value. The results of this analysis are obtained from questionnaires that have been distributed to 75 companies, consisting of 40 companies that adopt ERP system and 35 companies that do not adoption of ERP system, the samples obtained by each of only 30 companies so that there are 60 companies studied. The hypothesis in this study will be tested using Mann Whitney nonparametric analysis with SPSS to look for differences in the impact of the two types of firms. This analysis proves that the ERP system affects the relevance of accounting information consisting of three variables and firm performance on companies that adopt ERP systems.

Research Question: What are the accounting benefits perceived by accountants and internal auditors that entail through Enterprise Resource Planning (ERP) systems? Is there an interaction of ERP accounting benefits with the accountants’ and internal auditors’ satisfaction level in using ERP systems? Motivation: Many organizations are implementing ERP systems extensively while sharing a common database and being real-time. Past scholars summon empirical studies on ERP's impact on accounting benefits and user satisfaction. Therefore, this study was conducted from accountants’ and internal auditors’ perspective as recent scholars shed light on the cruciality of these two groups' perceptions as key ERP users. Idea: This study examines the accounting benefits that entail through the adoption of ERP systems by Sri Lankan companies with regard to ERP user satisfaction from the perspective of accountants and internal auditors. Data: The data were collected from 38 accountants and 19 internal auditors across 24 companies that are implementing ERP systems for more than four years. Tools: A quantitative survey methodology is employed to draw empirical evidence. Findings: The findings confirm that organizational, operational (time), and IT accounting benefits derived from ERP systems significantly and positively influence ERP users' satisfaction. In contrast, operational accounting benefits (cost) received the lowest rating and did not significantly influence user satisfaction. Contribution: While these findings are valuable to accountants and internal auditors to better understand the ERP accounting benefits, ERP consultants and system providers also benefit from identifying ERP accounting features to uplift user satisfaction in developing countries.

Global and Malaysian Perspective Ahmad Saleh Shatat, Faculty of Business, Sohar University Sohar, Oman, and Zulkifli Mohamed Udin College of Business, Universiti Utara Malaysia, Kedah Darul Aman , Malaysia Abstract: Business management has entered the era of networking competition. This has moved the competition from a local to that of global business environments and from company against company to that of a supply chain against supply chain. Enterprise Resource Planning (ERP) system has become one of the main pre-requisites for many companies enabling them to compete in the local and global market, a price of entry to gain a competitive advantage in the global economy, and a backbone for e-business as well as for the whole supply chain. Many companies are still reluctant to implement ERP system and therefore they will not be able to connect their supply chain with several global and local companies where ERP system has become a prerequisite and a price of entry for the global economy. This study has investigated the main issues, challenges and the benefits of ERP system. ERP systems will be the price of entry and a prerequisite for many companies enabling them to run their business smoothly and effectively, and to be able to connect with other companies in the current global network economy. 1. ERP Global Change The big five ERP venders in the ERP global market are SAP, Oracle, PeopleSoft, J.D. Edwards, and Baan. In 1999 they acquired 59 percent of ERP revenue and each has specialty in a particular module area, for example, SAP specialized in logistics, Oracle in financials, PeopleSoft in human resources management, and Bann in manufacturing. SAP was the largest ERP vendor among them with revenue of $5 billion, and then Oracle with $2.4 billion in sales, followed by PeopleSoft with $1.3 billion, J.D. Edwards with $979 million, and finally Baan with sales of $743 million. The most three famous ERP venders in ERP market are SAP, Oracle, and PeopleSoft. Figure 1.1 describes the three biggest ERP venders’ competitors in the global market (McAdam & Galloway, 2005; Holland & Light, 1999)

Enterprise Resource Planning (ERP) systems offer various functionalities to support an organization’s core functions. However, many anticipated benefits often need to materialize due to business context changes and users’ high expectations. Continuous adaptation and improvement are necessary to address user disappointments. This research focuses on ERP systems, exploring key factors influencing the success of their implementation. Recognizing challenges in ERP system implementation, this study provides a comprehensive literature review, identifying essential and contemporary Critical Success Factors (CSFs) influenced by technological advancements. Addressing challenges specific to the wood industry, this research introduces additional industry-adapted CSFs, including industry adaptability, integration with production machinery, effective warehouse management, and supply chain tracking. Furthermore, this paper emphasizes the need for continuous adaptation and improvement of ERP systems, especially in light of current trends and technological achievements. This study recommends a holistic approach, considering traditional or essential CSFs while adapting to new trends. Critical success factors in ERP implementation in the next decade involve considering cloud technology, artificial intelligence and machine learning, data security, mobile access, IoT integration, user experience, and training. The main objective of this paper is to identify the latest CSFs in ERP implementation. This research highlights essential success factors in ERP implementation, and contemporary trends in ERP implementation with a particular focus on the specifics of wood industry. While organizations should aim to maximize the potential of ERP systems, they should also acknowledge the crucial role played by human intervention in the effective and responsible implementation of artificial intelligence.

Most enterprise systems (ES) solutions have evolved with the technological factors of flexibility, modularity and integration embedded to fit both business and information technology (IT) requirements for many organizations. Recently, Enterprise Resource Planning (ERP) and business-to-business electronic business (e-business) have received much attention within both the practitioner and academic communities, especially concerning the technological factors. The purpose of this study is to develop a framework that could be used to investigate a possible relationship between ERP and other ES systems with the factors of flexibility, integration and modularity for e-business. In the 1990's, ERP systems were introduced to fulfill some of the technological requirements across functional areas within a corporate boundary. Moreover, with the exponential growth of Internet technology and the emergence of e-business, the focus of ERP systems has changed from an integrated functional focus within an organization to one reaching outside the organization throughout the value chain system. It is expected that an ERP system can facilitate an e-business effort of an organization. In order to serve as a platform for e-business, an ERP system must also be able to be extended to support a range of external constituents for a firm. The process must involve an investigation of ERP technological factors along with any other emerging ES solution of the firm. This study investigates ERP and other ES systems for e-business with a focus on the technological factors of flexibility, integration, and modularity.

This abstract delves into the realm of manufacturing productivity enhancement through the review of AI-driven supply chain management (SCM) optimization and Enterprise Resource Planning (ERP) systems integration. As industries strive for operational excellence, the convergence of artificial intelligence (AI) and supply chain management emerges as a transformative force in driving efficiency, agility, and competitiveness. Through a comprehensive analysis, this abstract examines the synergistic relationship between AI-driven SCM optimization and the integration of ERP systems, elucidating their collective impact on manufacturing productivity. AI-driven SCM optimization encompasses a spectrum of technologies and methodologies, including predictive analytics, machine learning, and autonomous decision-making systems, aimed at optimizing various facets of the supply chain, from demand forecasting and inventory management to production planning and logistics optimization. By harnessing the power of AI, manufacturers can enhance forecasting accuracy, reduce lead times, optimize inventory levels, and mitigate supply chain disruptions, thereby improving overall productivity and customer satisfaction. Integration of ERP systems plays a complementary role in manufacturing productivity enhancement by providing a centralized platform for data management, process automation, and cross-functional collaboration. Through seamless integration with AI-driven SCM optimization tools, ERP systems enable real-time data exchange, actionable insights, and end-to-end visibility across the supply chain, facilitating informed decision-making and agile response to dynamic market conditions. Drawing insights from case studies and industry examples, this abstract highlights best practices, challenges, and emerging trends in AI-driven SCM optimization and ERP systems integration. Strategies for successful implementation, including organizational readiness assessment, change management, and stakeholder engagement, are discussed to guide manufacturers in unlocking the full potential of these transformative technologies. In conclusion, the convergence of AI-driven SCM optimization and ERP systems integration offers a compelling pathway for enhancing manufacturing productivity, driving operational excellence, and sustaining competitive advantage in the digital era.. Keywords: Artificial Intelligence, Supply Chain Management, Enterprise Resource Planning, Manufacturing Productivity, AI Integration, Predictive Analytics.

ERP systems have great influence on the tax auditing in enterprises implemented by the taxation authorities. This paper analyzes the influence caused by ERP on tax auditing and the countermeasures can be taken by the tax auditors. The major influence caused by ERP on tax auditing is as follows. The visible tax auditing clues reduce. The emphases of tax auditing should be changed. And the data collection of tax auditing becomes more difficult. In order to deal with the influence caused by ERP systems, the tax auditors should take the following countermeasures: Strengthen the controls before the establishment and during the operation of ERP Systems. Restrict enterprise's financial activities and tax behaviors according to the law. Choose tax auditing method carefully in ERP Systems. And develop tax auditing software adapted to the ERP environment.

Process mining techniques provide capabilities for discovering the real business process flows from data, and compare expected and actual behaviors. Actual behaviors, in many cases, are obtained from Enterprise Resource Planning (ERP) systems and other enterprise information systems transaction logs. These transaction logs provide valuable insight into the companies' business processes. They traditionally hold a large amount of data in a set of conceptual documents related to each other through one-to-many and many-to-many relations, where information changes occur in transactions. Underlying data model gives rise to complex interactions between multiple data objects without a clear notion of a unique case identifier in an isolated process. However, enterprise process mining techniques can be applied only to event logs containing event data related to one notion of process instances. Within ERP systems, such event logs are not explicitly given and substantial domain knowledge is required to select the right data from multiple tables in relational databases. In order to respond to this need, in this paper we present an abstract syntax of domain specific language (DSL) for facilitating the extraction of an appropriate dataset from ERP systems by domain experts, and its conversion into event log based on XES IEEE standard. It is developed specifically to describe behavior over complex data from ERP systems in terms of multiple interacting artifacts. The goal is to align the data and process perspectives, supporting extraction of complex ambiguous cases, affected by data convergence and data divergence problems. The basic concepts of the language as well as principles are discussed in depth in this paper.

Background: Public sector organisations encounter many challenges because of their complex legislative requirements, social responsibilities and higher public expectations. In the early 1980s, governments worldwide started experimenting with improving functions and processes through enterprise resource planning (ERP) systems. Objective: This study investigated the feasibility of South African government institutions in adopting a guideline that will assist in implementing a sustainable ERP system to improve their information systems strategy. Method: This study followed the qualitative dominating mixed research methodology. A survey was distributed to 20 participants with closed-ended questions to collect quantitative data and open-ended questions to collect qualitative data. Results: Thirteen factors that allow ERP systems to be successfully implemented were identified. Some of the factors included effective change management policies, end-user specialised knowledge, organisation culture fit, top management support, ERP training before and post-implementation, visibility of activities throughout the workflow, and willingness to change. Sixteen issues that restrict ERP implementation were also identified. Some of the restricting factors include ERP system complexity, high levels of customisation, inadequate flexibility, budget, maintenance costs, lack of vendor support, implementation delays and cost overruns. The current state of ERP implementation in the investigated organisation is of acceptance with growth being achieved gradually and steadily. Conclusion: The proposed framework provides core competencies such as top management support, ERP training before and post-implementation, and effective change management policies among others, that can be used to establish corrective measures before and during the installation of ERP systems. Contribution: This study contributed to the body of knowledge by identifying the success and hindering factors of ERP system implementation. The proposed framework outlines guidelines for organisations to successfully adopt and implement ERP systems.

Background: Public sector organisations encounter many challenges because of their complex legislative requirements, social responsibilities and higher public expectations. In the early 1980s, governments worldwide started experimenting with improving functions and processes through enterprise resource planning (ERP) systems. Objective: This study investigated the feasibility of South African government institutions in adopting a guideline that will assist in implementing a sustainable ERP system to improve their information systems strategy. Method: This study followed the qualitative dominating mixed research methodology. A survey was distributed to 20 participants with closed-ended questions to collect quantitative data and open-ended questions to collect qualitative data. Results: Thirteen factors that allow ERP systems to be successfully implemented were identified. Some of the factors included effective change management policies, end-user specialised knowledge, organisation culture fit, top management support, ERP training before and post-implementation, visibility of activities throughout the workflow, and willingness to change. Sixteen issues that restrict ERP implementation were also identified. Some of the restricting factors include ERP system complexity, high levels of customisation, inadequate flexibility, budget, maintenance costs, lack of vendor support, implementation delays and cost overruns. The current state of ERP implementation in the investigated organisation is of acceptance with growth being achieved gradually and steadily. Conclusion: The proposed framework provides core competencies such as top management support, ERP training before and post-implementation, and effective change management policies among others, that can be used to establish corrective measures before and during the installation of ERP systems. Contribution: This study contributed to the body of knowledge by identifying the success and hindering factors of ERP system implementation. The proposed framework outlines guidelines for organisations to successfully adopt and implement ERP systems.

This study investigates the impact of Enterprise Resource Planning (ERP) systems on operational efficiency at Amazon, a global leader in e-commerce and cloud computing. ERP systems are integral to modern business, integrating core processes and facilitating data-driven decision- making. Amazon employs a sophisticated mix of commercial (e.g., SAP, Oracle) and proprietary ERP solutions to manage its vast and complex operations, including procurement, inventory, warehouse management, and order fulfilment. The primary purpose of this research is to understand ERP's role in Amazon's supply chain and logistics, analyse its impact on key performance indicators such as cost reduction, order accuracy, and process automation, and identify potential best practices. The study utilized a hybrid research methodology, commencing with an exploratory phase involving literature review and analysis of secondary data, followed by a descriptive phase centred on a quantitative survey. The survey gathered data from 92 professionals with experience in ERP systems and operations, many familiar with Amazon or similar large-scale environments. Key findings indicate a strong positive perception of ERP's impact on reducing order processing time, enhancing inventory accuracy, and improving interdepartmental coordination. However, challenges related to system usability, technical glitches, and the need for comprehensive user training were also identified. The study concludes that while ERP systems significantly contribute to Amazon's operational prowess, continuous improvement in user experience and ongoing support are crucial. Recommendations focus on enhancing user training, simplifying interfaces, improving system performance, establishing robust feedback mechanisms, and leveraging key performance indicators to track ERP impact. This research contributes to the understanding of ERP effectiveness in high-volume, technology- driven organizations. List of Abbreviations: ERP: Enterprise Resource Planning; KPI: Key Performance Indicator; AWS: Amazon Web Services; UX: User Experience.