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Enterprise Architectures (EA) consists of many architecture elements, which stand in manifold relationships to each other. Therefore Architecture Analysis is important and very difficult for stakeholders. Due changing an architecture element has impacts on other elements different stakeholders are involved. In practice EAs are often analyzed using visualizations. This article aims at contributing to the field of visual analytics in EAM by analyzing how state of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study and accomplishing them in a master’s level class with students.
In times of dynamic markets, enterprises have to be agile to be able to quickly react to market influences. Due to the increasing digitization of products, the enterprise IT often is affected when business models change. Enterprise Architecture Management (EAM) targets a holistic view of the enterprise’ IT and their relations to the business. However, Enterprise Architectures (EA) are complex structures consisting of many layers, artifacts and relationships between them. Thus, analyzing EA is a very complex task for stakeholders. Visualizations are common vehicles to support analysis. However, in practice visualization capabilities lack flexibility and interactivity. A solution to improve the support of stakeholders in analyzing EAs might be the application of visual analytics. Starting from a systematic literature review, this article investigates the features of visual analytics relevant for the context of EAM.
Analysis is an important part of the enterprise architecture management process. Prior to decisions regarding transformation of the enterprise architecture, the current situation and the outcomes of alternative action plans have to be analysed. Many analysis approaches have been proposed by researchers and current enterprise architecture management tools implement analysis functionalities. However, few work has been done structuring and classifying enterprise architecture analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for enterprise architecture analysis classification. For evaluation, a collection of enterprise architecture analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for enterprise architecture analysis classification has been derived and suggestions for further development are drawn.
Digitalization and enterprise architecture management: a perspective on benefits and challenges
(2023)
Many companies digitally transform their business models, processes, and services. They have also been using Enterprise Architecture Management approaches for a long time to synchronize corporate strategy and information technology. Such digitalization projects bring different challenges for Enterprise Architecture Management. Without understanding and addressing them, Enterprise Architecture Management projects will fail or not deliver the expected value. Since existing research has not yet addressed these challenges, they were investigated based on a qualitative expert study with leading industry experts from Europe. Furthermore, potential benefits of digitalization projects for Enterprise Architecture Management were researched. Our results provide a theoretical framework consisting of five identified challenges, triggers and a number of benefits. Furthermore, we discuss in what ways digitalization and EAM is a promising topic for future research.
Neue Modelle für digitale Unternehmensarchitekturen mit Big Data, Services & Cloud Computing, mobilen Systemen, Internet of Things sowie Industrie 4.0 Ökosystemen machen eine enge Kooperation verschiedener Partner aus Wissenschaft, Anwendungsunternehmen, öffentlichen Organisationen, Softwarehersteller und IT- Dienstleister notwendig. Ziel dieser Zusammenarbeit ist die Zusammenführung neuer Konzepte und Möglichkeiten der Informationstechnologie zur bestmöglichen Unterstützung sich verändernder Unternehmensziele und -strategien. Software- und Unternehmensarchitekturen spielen hierbei eine zentrale Rolle. So werden Anforderungen bezüglich Flexibilität und Agilität in digitalen Unternehmen wesentlich durch serviceorientierte Ansätze unterstützt. Der Ordnungsgrad und die kosteneffiziente Gestaltung komplexer IT-Landschaften soll durch Digital Enterprise Architecture Management deutlich verbessert werden – passend zu neuen Möglichkeiten von Services & Cloud Computing, Big Data, sowie kollaborativen Geschäftsprozessen.
Digitalization of products and services commonly causes substantial changes in business models, operations, organization structures and IT infrastructures of enterprises. Motivated by experiences and observations from digitalization projects, the paper investigates the effects of digitalization on enterprise architectures (EA). EA models serve as representation of business, information system and technical aspects of an enterprise to support management and development. By comparing EA models before and after digitalization, the paper analyzes the kinds of changes visible in the EA model. The most important finding is that newly created digitized products and the associated (product)- and enterprise architecture are no longer properly integrated into the overall architecture and even exist in parallel. Thus, the focus of this work is on showing these parallel architectures and proposing derivations for a better integration.
Digital technologies are main strategic drivers for digitalization and offer ubiquitous data availability, unlimited connectivity, and massive processing power for a fundamentally changing business. This leads to the development and application of intelligent digital systems. The current state of research and practice of architecting digital systems and services lacks a solid methodological foundation that fully accommodates all requirements linked to efficient and effective development of digital systems in organizations. Research presented in this paper addresses the question, how management of complexity in digital systems and architectures can be supported from a methodological perspective. In this context, the current focus is on a better understanding of the causes of increased complexity and requirements to methodological support. For this purpose, we take an enterprise architecture perspective, i.e. how the introduction of digital systems affects the complexity of EA. Two industrial case studies and a systematic literature analysis result in the proposal of an extended Digital Enterprise Architecture Cube as framework for future methodical support.
Current approaches for enterprise architecture lack analytical instruments for cyclic evaluations of business and system architectures in real business enterprise system environments. This impedes the broad use of enterprise architecture methodologies. Furthermore, the permanent evolution of systems desynchronizes quickly model representation and reality. Therefore we are introducing an approach for complementing the existing top-down approach for the creation of enterprise architecture with a bottom approach. Enterprise Architecture Analytics uses the architectural information contained in many infrastructures to provide architectural information. By applying Big Data technologies it is possible to exploit this information and to create architectural information. That means, Enterprise Architectures may be discovered, analyzed and optimized using analytics. The increased availability of architectural data also improves the possibilities to verify the compliance of Enterprise Architectures. Architectural decisions are linked to clustered architecture artifacts and categories according to a holistic EAM Reference Architecture with specific architecture metamodels. A special suited EAM Maturity Framework provides the base for systematic and analytics supported assessments of architecture capabilities.
The internet of things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud environments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors for living and adaptable ecosystems are currently providing the logical foundation for resilient run-time environments with serviceoriented digitization architectures and for self-optimizing intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution of information systems with digital architecture in the context of the ongoing digital transformation. The goal is to support flexible and agile transformations for both business and related information systems through adaptation and dynamical evolution of their digital architectures. The present research paper investigates mechanisms of decision analytics for digitization architectures, putting a spotlight to internet of things micro-granular architectures, by extending original enterprise architecture reference models with digitization architectures and their multi-perspective architectural decision management.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. The Internet of Things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and service-oriented enterprise architectures. Our aim is to support flexibility and agile transformations for both business domains and related information technology. The present research paper investigates mechanisms for decision analytics in the context of multi-perspective explorations of enterprise services and their digital enterprise architectures by extending original architecture reference models with state of art elements for agile architectural engineering for the digitization and collaborative architectural decision support. The paper’s context focuses on digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems. We are putting a spotlight on the example domain – Internet of Things.
Today, many companies are adapting their strategy, business models, products, services as well as business processes and information systems in order to expand their digitalization level through intelligent systems and services. The paper raises an important question: What are cognitive co-creation mechanisms for extending digital services and architectures to readjust the usage value of smart services? Typically, extensions of digital services and products and their architectures are manual design tasks that are complex and require specialized, rare experts. The current publication explores the basic idea of extending specific digital artifacts, such as intelligent service architectures, through mechanisms of cognitive co-creation to enable a rapid evolutionary path and better integration of humans and intelligent systems. We explore the development of intelligent service architectures through a combined, iterative, and permanent task of co-creation between humans and intelligent systems as part of a new concept of cognitively adapted smart services. In this paper, we present components of a new platform for the joint co-creation of cognitive services for an ecosystem of intelligent services that enables the adaptation of digital services and architectures.
Big Data und Cloud Systeme werden zunehmend von mobilen, benutzerzentrierten und agil veränderbaren Informationssystemen im Kontext von digitalen sozialen Netzwerken genutzt. Metaphern aus der Biologie für lebendige und selbstheilende Systeme und Umgebungen liefern die Basis für intelligente adaptive Informationssysteme und für zugehörige serviceorientierte digitale Unternehmensarchitekturen. Wir berichten über unsere Forschungsarbeiten über Strukturen und Mechanismen adaptiver digitaler Unternehmensarchitekturen für die Entwicklung und Evolution von serviceorientierten Ökosystemen und deren Technologien wie Big Data, Services & Cloud Computing, Web Services und Semantikunterstützung. Für unsere aktuellen Forschungsarbeiten nutzen wir praxisrelevante SmartLife Szenarien für die Entwicklung, Wartung und Evolution zukunftsgerechter serviceorientierter Informationssysteme. Diese Systeme nutzen eine stark wachsende Zahl externer und interner Services und fokussieren auf die Besonderheiten der Weiterentwicklung der Informationssysteme für integrierte Big Data und Cloud Kontexte. Unser Forschungsansatz beschäftigt sich mit der systematischen und ganzheitlichen Modellbildung adaptiver digitaler Unternehmensarchitekturen - gemäß standardisierter Referenzmodelle und auf Standards aufsetzenden Referenzarchitekturen, die für besondere Einsatzszenarien auch bei kleineren Anwendungskontexten oder an neue Kontexte einfacher adaptiert werden können. Um Semantik-gestützte Analysen zur Entscheidungsunterstützung von System- und Unternehmensarchitekten zu ermöglichen, erweitern wir unser bisheriges Referenzmodell für ITUnternehmensarchitekturen ESARC – Enterprise Services Architecture Reference Cube – um agile Mechanismen der Adaption und Konsistenzbehandlung sowie die zugehörigen Metamodelle und Ontologien für Digitale Enterprise Architekturen um neue Aspekte wie Big Data und Cloud Kontexte.
The Internet of Things (IoT), enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems with service oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision case management in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering for the digitization and architectural decision support.
Enterprises are transforming their strategy, culture, processes, and their information systems to enlarge their digitalization efforts or to approach for digital leadership. The digital transformation profoundly disrupts existing enterprises and economies. In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies: The Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, microservices, or other micro-granular elements. Architecting micro-granular structures have a substantial impact on architecting digital services and products. The change from a closed-world modeling perspective to more flexible Open World of living software and system architectures defines the context for flexible and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are revealing multiple perspectives of digital enterprise architecture and decisions to effectively support value and service oriented software systems for intelligent digital services and products.
Artificial Intelligence-based Assistants AIAs are spreading quickly both in homes and offices. They already have left their original habitats of "intelligent speakers" providing easy access to music collections. The initiated a multitude of new devices and are already populating devices such as TV sets. Characteristic for the intelligent digital assistants is the formation of platforms around their core functionality. Thus, AIS capabilities of the assistants are used to offer new services and create new interfaces for business processes. There are positive network effects between the assistants and the services as well as within the services. Therefore, many companies see the need to get involved in the field of digital assistants but lack a framework to align their initiatives with their corporate strategies. In order to lay the foundation for a comprehensive method, we are therefore investigating intelligent digital assistants. Based on this analysis, we are developing a framework of strategic opportunities and challenges.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. The digitization of software-intensive products and services is enabled basically by four megatrends: Cloud computing, big data mobile systems, and social technologies. This disruptive change interacts with all information processes and systems that are important business enablers for the current digital transformation. The internet of things, social collaboration systems for adaptive case management, mobility systems and services for big data in cloud services environments are emerging to support intelligent user-centered and social community systems. Modern enterprises see themselves confronted with an ever growing design space to engineer business models of the future as well as their IT support, respectively. The decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures (EA), is duly needed. With the advent of intelligent user-centered and social community systems, the challenging decision processes can be supported in more flexible and intuitive ways. Tapping into these systems and techniques, the engineers and managers of the enterprise architecture become part of a viable enterprise, i.e. a resilient and continuously evolving system that develops innovative business models.
New business opportunities appeared using the potential of the Internet and related digital technologies, like the Internet of Things, services computing, artificial intelligence, cloud, edge, and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber-physical systems. Companies are transforming their strategy and product base, as well as their culture, processes and information systems to adopt digital transformation or to approach for digital leadership. Digitalization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. Digitalization has a substantial impact for architecting the open and complex world of highly distributed digital servcies and products, as part of a new digital enterprise architecture, which structure and direct service-dominant digital products and services. The present research paper investigates mechanisms for supporting the evolution of digital enterprise architectures with user-friendly methods and instruments of interaction, visualization, and intelligent decision management during the exploration of multiple and interconnected perspectives by an architecture management cockpit.
Presently, many companies are transforming their strategy and product base, as well as their culture, processes and information systems to become more digital or to approach for a digital leadership. In the last years new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, edge and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of micro-granular system architectures defines the moving context for adaptable systems. We are focusing on a continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, as part of a new digital enterprise architecture for service dominant digital products.
Digitization fosters the development of IT environments with many rather small structures, like Internet of Things (IoT), microservices, or mobility systems. They are needed to support flexible and agile digitized products and services. The goal is to create service-oriented enterprise architectures (EA) that are self optimizing and resilient. The present research paper investigates methods for decision-making concerning digitization architectures for Internet of Things and microservices. They are based on evolving enterprise architecture reference models and state of the art elements for architectural engineering for microgranular systems. Decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures, is sorely needed. The challenging of the decision processes can be supported with in a more flexible and intuitive way by an architecture management cockpit.
Digitization of societies changes the way we live, work, learn, communicate, and collaborate. In the age of digital transformation IT environments with a large number of rather small structures like Internet of Things (IoT), microservices, or mobility systems are emerging to support flexible and agile digitized products and services. Adaptable ecosystems with service oriented enterprise architectures are the foundation for self-optimizing, resilient run-time environments and distributed information systems. The resulting business disruptions affect almost all new information processes and systems in the context of digitization. Our aim are more flexible and agile transformations of both business and information technology domains with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision-controlled digitization architectures for Internet of Things and microservices by evolving enterprise architecture reference models and state of the art elements for architectural engineering for micro-granular systems.