Process Mining for Business Process Standardization in ERP Implementation Projects – An SAP S/4 HANA Case Study from Manufacturing

Organizations increasingly build operations on enterprise resource planning (ERP) systems. However, ERP implementation projects require significant process transformation and standardization to successfully use ERP systems. This article presents a case study in a manufacturing corporation to demonstrate how process mining can be used for process decisionmaking in an SAP S/4 HANA implementation project. In particular, the corporation implements process mining for the analysis of the SAP purchase-to-pay (“Purchas-ing”) and the order-to-cash (“Sales”) processes to determine whether the future to-be process should be standardized according to ERP standards, or to be individualized in a corporate-specific template. Further, process mining can be used to select suitable standard process specifications from the SAP Best Practices Explorer, as well as to analyze the required process changes before the launch of the new ERP system and process implementations

Design of Data-Driven Decision Support Systems for Business Process Standardization

Increasingly dynamic environments require organizations to engage in business process standardization (BPS) in response to environmental change. However, BPS depends on numerous contingency factors from different layers of the organization, such as strategy, business models (BMs), business processes (BPs) and application systems that need to be well-understood (“comprehended”) and taken into account by decision-makers for selecting appropriate standard BP designs that fit the organization. Besides, common approaches to BPS are non-data-driven and frequently do not exploit increasingly avail-able data in organizations. Therefore, this thesis addresses the following research ques-tion: “How to design data-driven decision support systems to increase the comprehen-sion of contingency factors on business process standardization?”. Theoretically grounded in organizational contingency theory (OCT), this thesis address-es the research question by conducting three design science research (DSR) projects to design data-driven decision support systems (DSSs) for SAP R/3 and S/4 HANA ERP systems that increase comprehension of BPS contingency factors. The thesis conducts the DSR projects at an industry partner within the context of a BPS and SAP S/4 HANA transformation program at a global manufacturing corporation. DSR project 1 designs a data-driven “Business Model Mining” system that automatical-ly “mines” BMs from data in application systems and represents results in an interactive “Business Model Canvas” (BMC) BI dashboard to comprehend BM-related BPS con-tingency factors. The project derives generic design requirements and a blueprint con-ceptualization for BMM systems and suggests an open, standardized reference data model for BMM. The project implements the software artifact “Business Model Miner” in Microsoft Azure / PowerBI and demonstrates technical feasibility by using data from an educational SAP S/4 HANA system, an open reference dataset, and three real-life SAP R/3 ERP systems. A field evaluation with 21 managers at the industry partner finds differences between tool results and BMCs created by managers and thus the po-tential for a complementary role of BMM tools to enrich the comprehension of BMs. A further controlled laboratory experiment with 142 students finds significant beneficial impacts on subjective and objective comprehension in terms of effectiveness, efficiency, and relative efficiency. Second, DSR project 2 designs a data-driven process mining DSS “KeyPro” to semi-automatically discover and prioritize the set of BPs occurring in an organization from log data to concentrate BPS initiatives on important BPs given limited organizational resources. The project derives objective and quantifiable BP importance metrics from BM and BPM literature and implements KeyPro for SAP R/3 ERP and S/4 HANA sys-tems in Microsoft SQL Server / Azure and interactive PowerBI dashboards. A field evaluation with 52 managers compares BPs detected manually by decision-makers against BPs discovered by KeyPro and reveals significant differences and a complemen-tary role of the artifact to deliver additional insights into the set of BPs in the organiza-tion. Finally, a controlled laboratory experiment with 30 students identifies the dash-boards with the lowest comprehension for further development. Third, OCT requires organizations to select a standard BP design that matches contin-gencies. Thus, DSR project 3 designs a process mining DSS to select a standard BP from a repository of different alternative designs based on the similarity of BPS contin-gency factors between the as-is process and the to-be standard processes. DSR project 3 thus derives four different process model variants for representing BPS contingency factors that vary according to determinant factors of process model comprehension (PMC) identified in PMC literature. A controlled laboratory evaluation with 150 stu-dents identifies significant differences in PMC. Based on laboratory findings, the DSS is implemented in the BPM platform “Apromore” to select standard BP reference mod-els from the SAP Best Practices Explorer for SAP S/4 HANA and applied for the pur-chase-to-pay and order-to-cash process of a manufacturing company

Leveraging Big Data for M&A: Towards Designing Process Mining Analyses for Process Assessment in IT Due Diligence

The success of mergers & acquisitions (M&A) depends on the buyer\u27s adequate due diligence (DD) assessment of the target firm. Assessing the target\u27s IT-enabled processes recently emerged as a novel information technology DD (IT DD) responsibility. However, it remains unclear how to operationalize and conduct the process assessment in IT DD. To address this challenge, we propose the big data analytics technology process mining (PM) and follow a design science research approach, based on literature and 12 interviews, to reveal and operationalize requirements for process assessment in IT DD, demonstrate PM to measure the operationalized requirements, and derive design principles and enabling factors to guide the design, implementation, and use of PM for process assessment in IT DD. Consequently, our study contributes to research on IT DD, M&A, and PM and provides practitioners with design knowledge and a prototypical PM artifact to leverage PM for process assessment in IT DD

Multikonferenz Wirtschaftsinformatik (MKWI) 2016: Technische Universität Ilmenau, 09. - 11. März 2016; Band II

Übersicht der Teilkonferenzen Band II • eHealth as a Service – Innovationen für Prävention, Versorgung und Forschung • Einsatz von Unternehmenssoftware in der Lehre • Energieinformatik, Erneuerbare Energien und Neue Mobilität • Hedonische Informationssysteme • IKT-gestütztes betriebliches Umwelt- und Nachhaltigkeitsmanagement • Informationssysteme in der Finanzwirtschaft • IT- und Software-Produktmanagement in Internet-of-Things-basierten Infrastrukturen • IT-Beratung im Kontext digitaler Transformation • IT-Sicherheit für Kritische Infrastrukturen • Modellierung betrieblicher Informationssysteme – Konzeptuelle Modelle im Zeitalter der digitalisierten Wirtschaft (d!conomy) • Prescriptive Analytics in I

Industrial internet and its role in process automation

Modern process automation undergoes a major shift in the way it addresses conventional challenges. Moreover, it is adapting to the newly arising challenges due to changing business scenarios. Nowadays, the areas of the automation that recently were rather separate start to merge and the border between them is fading. This situation only adds struggle to the already highly competitive production industry. In order to be successful, companies should adopt new approaches to the way their processes are automated, controlled, and managed. One of these approaches is the so-called Industrial Internet. It is the next step after the traditional paradigm of the process automation pyramid that leads to the new vision of interconnected processes, services, machines and people. However, general company does not usually eager to implement the new technology to its business. One of the reasons for this is that it does not see the advantages that the Industrial Internet brings. This is due to the lack of sufficient number of successful implementation examples in various industrial areas and of clear business scenarios for the use of the Industrial Internet. Aim of the presented thesis is to create a convincing Industrial Internet application scenario. For the implementation, a mineral concentration plant was chosen as one of the industrial premises that possesses the shortage of the Industrial Internet examples. Literature review section describes the process automation state of art. It lists and reviews the research and development initiatives related to the Industrial Internet. Moreover, the Industrial Internet fundamentals are given. Finally, it describes the Industrial Internet applications and the case studies. In the practical part, at first, the description of the mineral concentration plant is given. Then, the next section describes the Industrial Internet application scenario. In the following section technical guidelines for the system implementation are given. Also, in the concluding part of the thesis the future direction of research work are discussed

Digital transformation and business model innovation : a multiple case study of consulting companies from Germany

This dissertation provides a status quo of the digital transformation within the German IT consulting industry in 2022 and examines the influence of digitalization on the business model (BM) development of consultancies. The paper studies the determinants which led consultancies to arrive at their current digitalization level, how their current BMs are characterized as well as how the development process induced by digitalization is composed, and eventually which success factors need to be fulfilled to overcome potential future growth barriers. In the literature review, definitions of the concept of BM and the innovation on BMs are discussed. Based on those insights, the characteristics of BMs in the consulting industry are identified and a deepened understanding of the phenomenon on digitalization is created. Grounded on the theoretical insights, a multiple case study spanning four different IT consulting firms is performed which investigates the business model developments of those consultancies by conducting two semi-structured interviews with related consultants per case complemented with secondary data generating data triangulation. The dissertation identifies changing requirements of stakeholders and in particular clients as the most relevant determinants for business model innovation. The findings of the thesis stress the importance of an outbalanced focus on the people business and the technological aspects of IT consulting. As most critical success factors a change affine mindset and company culture have been identified which embraces that mindset and consequently enables an organizational structure to execute the willingness for change.Esta dissertação fornece um status da transformação digital na indústria alemã de consultoria informática em 2022 e examina a influência da digitalização no desenvolvimento do modelo de negócio (BM) das consultorias. O artigo estuda os determinantes que levaram as consultorias a chegar ao seu atual nível de digitalização, como são caracterizados os seus atuais BMs, como é composto o processo de desenvolvimento induzido pela digitalização, e eventualmente os fatores de sucesso que precisam de ser cumpridos para superar potenciais barreiras de crescimento futuro. Na revisão da literatura, são discutidas definições do conceito de BM e inovação em BMs. Com base nestes conhecimentos, são identificadas as características de BMs na indústria de consultoria ed é criada uma compreensão profunda do fenómeno da digitalização. Com base nos conhecimentos teóricos, é realizado um estudo de caso múltiplo abrangendo quatro empresas de consultoria de IT diferentes que investiga os desenvolvimentos do BM dessas consultorias, conduzindo duas entrevistas semiestruturadas com consultores relacionados por caso, complementadas com dados secundários geradores de triangulação de dados. A dissertação identifica os requisitos em mudança das partes interessadas e, em particular, dos clientes como os determinantes mais relevantes para inovação do modelo de negócio. As conclusões da tese sublinham a importância de um enfoque desequilibrado no negócio das pessoas e nos aspetos tecnológicos da consultoria em IT. Como fatores de sucesso mais críticos, foi identificada uma mudança de mentalidade e cultura empresarial que abraça essa mentalidade e, consequentemente, permite uma estrutura organizacional para executar a vontade de mudança

Sustainability Reporting Process Model using Business Intelligence

Sustainability including the reporting requirements is one of the most relevant topics for companies. In recent years, many software providers have launched new software tools targeting companies committed to implementing sustainability reporting. But it’s not only companies willing to use their Business Intelligence (BI) solution, there are also basic principles such as the single source of truth and tendencies to combine sustainability reporting with the financial reporting (Integrated Reporting) The IT integration of sustainability reporting has received limited attention by scientific research and can be facilitated using BI systems. This has to be done both to anticipate the economic demand for integrated reporting from an IT perspective as well as for ensuring the reporting of revisable data. Through the adaption of BI systems, necessary environmental and social changes can be addressed rather than merely displaying sustainability data from additional, detached systems or generic spreadsheet applications. This thesis presents research in the two domains sustainability reporting and Business Intelligence and provides a method to support companies willing to implement sustainability reporting with BI. SureBI presented within this thesis is developed to address experts from both sustainability and BI. At first BI is researched from a IT and project perspective and a novel BI reporting process is developed. Then, sustainability reporting is researched focusing on the reporting content and a sustainability reporting process is derived. Based on these two reporting processes SureBI is developed, a step-by-step process method, aiming to guide companies through the process of implementing sustainability reporting using their BI environment. Concluding, an evaluation and implementation assesses the suitability and correctness of the process model and exemplarily implements crucial IT tasks of the process. The novel combination of these two topics indicates challenges from both fields. In case of BI, users face problems regarding historically grown systems and lacking implementation strategies. In case of sustainability, the mostly voluntary manner of this reporting leads to an uncertainty as to which indicators have to be reported. The resulting SureBI addresses and highlights these challenges and provides methods for the addressing and prioritization of new stakeholders, the prioritization of the reporting content and describes possibilities to integrate the high amount of estimation figures using BI. Results prove that sustainability reporting could and should be implemented using existing BI solutions