An Event Data Extraction Approach from SAP ERP for Process Mining

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.

The article discusses the use of an intelligent Power Query system for processing data from SAP ERP. When used with SAP ERP data, Power Query can greatly simplify the data analysis process, as well as improve the accuracy and reliability of results. The article provides an overview of the main features of Power Query and how they can be used for data processing in conjunction with the SAP ERP system. It highlights the benefits of using Power Query, including speeding up data processing time, improving data accuracy, and the ability to easily exchange and reuse data processing procedures. Using Power Query to process and analyze bank statements via SAP ERP provides many advantages. Power Query's powerful data processing and transformation capabilities enable organizations to analyze their financial data quickly and accurately, making it easier to identify trends, improve decision-making and stimulate business growth. In addition, the integration of Power Query with SAP ERP provides organizations with a centralized representation of financial data in real time, which allows them to make informed decisions and optimize their activities. Using Power Query to analyze bank statements can also help organizations reduce manual data processing and minimize the risk of errors, increasing the accuracy and reliability of financial information. In general, Power Query offers a powerful solution for organizations seeking to optimize financial analysis processes and ensure business success.

Medical billing is a long chain of processes that cut across different sectors and institutions, evolving into a multimillion-dollar industry. Despite the emergence of institutional involvement in the practice, the parties involved face many challenges that hinder the successful management of the diverse process. Process mining uses computer-based tools and techniques to analyze business processes and ensure best practices for improving business operations as it has a track record of success in improving business processes and procedures. As research on process driving problem solving continues to grow, there is a need to start applying the tools and techniques to specific domain areas and bridge the gap between research, development and application. We demonstrated how process mining techniques can be applied to medical billing using the L * life cycle model from a structured perspective. We developed a handmade comprehensive medical billing process flow using domain knowledge reference and established some time perspective Key Performance Indicators (KPIs) of the billing process. We then explored the hospital billing event log generated from an enterprise resource planning (ERP) system to see how the "as-is" from the event log deviate from the generally known knowledge-based (handmade) model. Taking each trace of the event log as patient visit, we discover that about 63 % of all the visit were billed and also about 3 % billed got regretted. The event log used in this research does not capture the complete activity flow for a real-world medical billing system. Hence, we were not able to directly compare the process map with the model and give precise operational support

Enterprise Resource Planning (ERP) systems handle a huge amount of data related to the actual execution of business processes and the goal is to discover from transaction log a model of how the business processes are actually carried out. The authors' work captures the knowledge of existing approaches and tools in converting the data from transaction logs to event logs for process mining techniques. They conduct a detailed analysis of the artifact-centric approach concepts and describe its constructs by the ontological metamodel. The underlying logical and semantically rich structure of the approach is presented through the model definition. The paper specifies how concepts of the data source are mapped onto the concept of the event log. Dynamics NAV ERP system is used as an example to illustrate the data-oriented structure of ERP system.

Increasingly organizations are using process mining to understand the way that operational processes are executed. Process mining can be used to systematically drive innovation in a digitalized world. Next to the automated discovery of the real underlying process, there are process-mining techniques to analyze bottlenecks, to uncover hidden inefficiencies, to check compliance, to explain deviations, to predict performance, and to guide users towards “better” processes. Dozens (if not hundreds) of process-mining techniques are available and their value has been proven in many case studies. However, process mining stands or falls with the availability of event logs. Existing techniques assume that events are clearly defined and refer to precisely one case (i.e. process instance) and one activity (i.e., step in the process). Although there are systems that directly generate such event logs (e.g., BPM/WFM systems), most information systems do not record events explicitly. Cases and activities only exist implicitly. However, when creating or using process models “raw data” need to be linked to cases and activities. This paper uses a novel perspective to conceptualize a database view on event data. Starting from a class model and corresponding object models it is shown that events correspond to the creation, deletion, or modification of objects and relations. The key idea is that events leave footprints by changing the underlying database. Based on this an approach is described that scopes, binds, and classifies data to create “flat” event logs that can be analyzed using traditional process-mining techniques.

Main memory virtualization is used to expand the effective main memory capacity meaning that more virtual main memory is represented to guest operating systems than physical memory is actually available. This is done by compressing and uncompressing memory pages. Obviously the price for main memory virtualization is a higher CPU utilization, especially when dealing with high workloads. SAP ERP systems represent the backbone of today's enterprises and have a very high resource demand. The combination of main memory virtualization and SAP ERP system is of great importance but has not yet been thoroughly researched. This paper is the first approach to a quantitative research for evaluating the performance impact of memory virtualization on SAP ERP systems. We utilize a synthetic main memory benchmark, called Zachmanntest, to evaluate the performance impact of main memory virtualization on a SAP ERP system. As an exemplary main memory virtualization implementation IBM's Active Memory Expansion is used, where a so called expansion factor can be used to specify the size of the virtual main memory. Performance results show that the greater the expansion factor, the greater the performance impact. Regarding the peak performance, throughput of SAP ERP systems may be decreased till -17%, whereas the overall throughput of such systems may experience a decrease up to -42% when dealing with a very high compression factor.

Enterprise resource planning (ERP) systems play a critical role in supporting a firm’s operations. Due to this reliance, a firm interacts with both the ERP solution provider and the ERP vendor as both support and maintain this complex system. This study investigates the impact of relationship interactions and a firm’s information systems (IS) technical competence on a firm’s satisfaction with the ERP vendor. To this end, this paper develops and verifies a model in which a firm’s past interactions and internal IS technical abilities serve as the antecedents of the firm’s satisfaction with its ERP system and ERP vendor. Empirical data collected from a sample of 168 firms were analyzed. The results suggest a firm’s perception of vendor conflict handling, and trust in the ERP vendor do positively influence the firm’s satisfaction with the ERP vendor. IS technical competence and strategic role of IS have a positive impact on a firm’s successful experience with the ERP system which ultimately leads to satisfaction perceptions.

The worldwide installed base of Enterprise Resource Planning (ERP) systems has increased rapidly in size over the past 10 years now comprising tens of thousands of installations in large- and medium-sized organizations and millions of licensed users. Similar to traditional Information Systems (IS), ERP systems must be maintained and upgraded. It is therefore not surprising that EPP maintenance activities have become the largest budget provision in the IS departments of ERP-adopting organizations. Yet, there has been very limited study conducted on ERP maintenance activities. Are they simply instances of traditional software maintenance activities to which traditional software maintenance research findings can be generalized? Or are they fundamentally different activities, such that new research, specific to ERP maintenance, is required to help alleviate the ERP maintenance burden? This paper reports a case study of a large organization that implemented ERP (an SAP system) two years ago. From the case study and data collected, we observe that (1) an ERP-employing organization does not only maintain user change request but also implement maintenance introduced by the vendor; (2) request for user-support. concerning the ERP system usage, and training constitutes a main part of ERP maintenance activities; and (3) configuration is a major ERP maintenance component. We find that ERP maintenance activities are indeed different from traditional in-house software maintenance in a way that these maintenance activities cannot be sufficiently described by existing taxonomies used to classify traditional software maintenance activities. We propose a benefits-oriented taxonomy that better represents ERP enhancement maintenance activities.

Event logs recorded during the execution of business processes constitute a valuable source of information. Applying process mining techniques to them, event logs may reveal the actual process execution and enable reasoning on quantitative or qualitative process properties. However, event logs often contain sensitive information that could be related to individual process stakeholders through background information and cross-correlation. We therefore argue that, when publishing event logs, the risk of such re-identification attacks must be considered. In this paper, we show how to quantify the re-identification risk with measures for the individual uniqueness in event logs. We also report on a large-scale study that explored the individual uniqueness in a collection of publicly available event logs. Our results suggest that potentially up to all of the cases in an event log may be re-identified, which highlights the importance of privacy-preserving techniques in process mining.

Background: Standard operating procedure (SOP) is a series of business activities to achieve organisational goals, with each activity carried to be recorded and stored in the information system together with its location (e.g., SCM, ERP, LMS, CRM). The activity is known as event data and is stored in a database known as an event log.Objective: Based on the event log, we can calculate the fitness to determine whether the business process SOP is following the actual business process.Methods: This study obtains the event log from a terminal operating system (TOS), which records the dwelling time at the container port. The conformance checking using token-based replay method calculates fitness by comparing the event log with the process model.Results: The findings using the Alpha algorithm resulted in the most traversed traces (a, b, n, o, p). The fitness calculation returns 1.0 were produced, missing, and remaining tokens are replied to each of the other traces.Conclusion: Thus, if the process mining produces a fitness of more than 0.80, this shows that the process model is following the actual business process. Keywords: Conformance Checking, Dwelling time, Event log, Fitness, Process Discovery, Process Mining

This publication is devoted to the problem of informatization and automation of management at the enterprise. The study found that the use of innovative systems is becoming increasingly popular in the Ukrainian market. Automation plays a crucial role in ensuring the growth of efficiency indicators of economic activity, but among domestic enterprises, there is a problem in choosing the use of a particular information system. This article describes the main advantages and disadvantages of ERP and CRM systems. Approaches to definitions are defined, and the concepts of ERP and CRM as methodologies of effective resource planning and system of automation of interaction with clients are revealed. A comparative analysis of ERP and CRM systems is carried out. The main functions of CRM systems are studied, among which: are the formation of a single information client base; working time management; optimization of communications within the company; sales planning. The place of the customer in the customer relationship management system is determined. The main modules of the ERP system are analyzed, namely: finance, personnel, sales, procurement, production, logistics, service, research and development, and assets. A detailed description of the functional solution when using the resource management system is given. The main tools of ERP and CRM systems are identified. As a result of the analysis of the modern market of information systems the main suppliers of software products and their weight in the given market segment are defined. A number of software products of ERP and CRM systems popular in Ukraine have been studied. The level of implementation of CRM systems by industry structure is determined. It is established that the maximum result from the implementation of CRM systems is possible only when they are implemented together with the integrated internal ERP system.

The importance of project management in the modern world was analyzed. The problem of using softwaretools in project management was substantiated. A review of scientific works on the subject of the study was carried out.Four features that describe the need in project management tools were analyzed. A list of 10 alternative tools to MicrosoftProject was described. SWOT analysis of Microsoft Project was conducted too. Creation steps of the new softwareproduct “Daily ProM Software” were described. All buttons and their functions were justified. SWOT analysis of thedeveloped product was conducted too. The advantages of the program were described in the research.DAILY ProM is a process mining software tool that is used to analyze, visualize and improve business processes. It isan open-source software developed at Eindhoven University of Technology, and is available for free download from theProM website.With DAILY ProM, users can import event logs from various sources, such as ERP systems, workflow managementsystems, and databases. The software then uses process mining techniques to extract useful insights from the event logs,such as process flow, performance metrics, bottlenecks, and compliance issues.DAILY ProM supports a wide range of process mining techniques, including process discovery, conformancechecking, performance analysis, and social network analysis. It also provides a user-friendly interface that allows usersto easily visualize the extracted process models and analyze them using various interactive tools.Overall, DAILY ProM is a powerful tool for process mining, and is widely used by researchers, practitioners, andstudents in the field of business process management.

In response to the international trend, in recent years companieshave officially adopted the International Financial Reporting Standards (IFRSs) and need to perform upgrade or adjustment to their Enterprise Resource Planning (ERP) systemsfor the IFRS conversion. Information technology (IT) governance in an ERP system environment will become akey that cannot be ignored by the management. To investigate the impact of implementing IT governance in an ERP environment on the effectiveness of ERP implementation and IFRS conversion The findings are as follows: Effective IT governance in a company can improve the project performance of ERP implementation; The improvement of the information quality and system qualityofan ERP system candemonstrate the effectiveness of the IFRS conversion through the ERP system; The project performance of ERP implementation can improve the information quality and system quality of the ERP system as well as the effectiveness of the IFRS implementation.

Process Mining helps to analyze and interpret business processes using event logs of information systems as ground truth. It has been successfully applied to process-oriented enterprise systems but is less suited for communication- and document-oriented Enterprise Collaboration Systems (ECS). This is due to two core characteristics of ECS processes and process logging. On the one hand, ECS processes are highly unstructured as their usage is not related to predefined business processes. The usage of ECS is ad-hoc and flexible. On the other hand, ECS commonly provide rather low-level process logs, i. e., logged events are very fine-granular, and, thus hard to interpret. Both characteristics lead to so-called spaghetti process models, which are barely interpretable when applying “traditional” process mining to ECS. This work focuses on the second aspect, i. e., to solve the problem of too fine-granular process logs of ECS. A common solution and preprocessing step for this granularity challenge is event abstraction, i.e., converting low-level logs into more abstract high-level logs before applying further process mining analysis techniques. ECS logs come with special characteristics that have so far not been fully addressed by existing event abstraction approaches. We aim to close this gap with a tailored ECS event abstraction (ECSEA) approach that trains a model by comparing observed actual user activities (also named high-level traces) with the system-generated low-level traces. The model allows us to automatically convert historic and future low-level traces into abstracted high-level traces that can be used for Process Mining. This article describes the ECS event log characteristics, introduces the proposed ECSEA approach with the underlying algorithms, and shows a corresponding evaluation. Our two-fold evaluation shows that the algorithm produces accurate results. In the evaluation, we use both synthetic and real-world event data taken from a productive ECS with more than 4000 users currently running at a university. • Derivation of relevant low-level event log characteristics: Based on a comparison of low-level and related high-level event logs, we derive low-level event log characteristics. They serve as requirements for a novel event abstraction approach and are further used for a comparison of related approaches. • Conceptualization of a novel supervised event abstraction approach: The main contribution is a novel event abstraction algorithm, which is described and evaluated in this article.

Modern organisations currently face a multitude of technologies that are seeking to climb on to the budgetary agenda of management boards. Two of the main contenders are enterprise resource planning (ERP) and e-business related technologies. There appears to be a misunderstanding, which has not been well-publicised, regarding the relationship between ERP and e-business, particularly the viewpoint that ERP is a platform for e-business. This paper, based on research from an ongoing information systems (IS) investigation project at a large multinational company, examines this relationship. The paper discusses different scenarios of ERP implementation status that organisations may find themselves part of. It examines the components of e-business success, namely the visibility of information, processes and technology that will be either enabled or restricted by ERP. What transpires from this research is that, for many start-ups, e-business becomes synonymous with business in general. We argue that e-business should form part of the corporate strategy and that an IS or IT strategy should form the basis for determining ERP implementation structures, thereby ensuring that e-business requirements become the platform for ERP.