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The blockchain technology enables a common data basis between the participants. Entries are logged and the authenticity of the participants is guaranteed. In the case of a relationship between customers and producers, this would lead to verifiable cooperation, which would be a major step as companies enter into service contracts based on the flow of many small transactions through communication. This paper proposes an architecture that enables the creation and processing of orders between the customer and producers via a blockchain based production network. The handling of larger files which are traceable via the blockchain is also shown and the use of a public or permissioned blockchain for an application case is also considered.
To bring a pattern-based perspective to the SOA vs. microservices discussion, we qualitatively analyzed a total of 118 SOA patterns from 2 popular catalogs for their (partial) applicability to microservices. Patterns had to hold up to 5 derived microservices principles to be applicable. 74 patterns (63%) were categorized as fully applicable, 30 (25%) as partially applicable, and 14 (12%) as not applicable. Most frequently violated microservices characteristics werde Decentralization and Single System. The findings suggest that microservices and SOA share a large set of architectural principles and solutions in the general space of service-based systems while only having a small set of differences in specific areas.
Creating new business models, products or services is challenging in fast changing unpredictable environments. Often, product teams need to make many assumptions (e.g., assumptions about future demands) that might not be true. These assumptions impose risks to the success and these risks need to be mitigated early. One of the principles of the Lean Startup approach is to identify and prioritize the riskiest assumptions in order to validate them as early as possible. This helps to avoid wasting effort and time. In the literature there are several different methods for identifying and prioritizing the riskiest assumptions reported. However, only little research exists about the practical application of these methods in practice and how to teach them. In this paper, we present and empirically analyze a workshop format that we have developed for teaching the prioritization of Lean Startup assumptions. We aim at raising the awareness for assumption thinking among the participants and teach them through group work how to prioritize assumptions. The results of the analysis of a multitude of conducted workshops show that the applied method did lead to reasonable results and accompanying learning effects. In addition, the participants got aware of assumption thinking and liked learning in a practical way.
Enterprise Governance, Risk and Compliance (GRC) systems are key to managing risks threatening modern enterprises from many different angles. Key constituent to GRC systems is the definition of controls that are implemented on the different layers of an Enterprise Architecture (EA). As part of the compliance aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper we present a metamodel which links controls to the affected elements of an EA and supplies a way of expressing associated assessment techniques and results. We complement the metamodel with an expository instantiation in a cockpit for control compliance applied in an international enterprise in the insurance industry.
Objective: This paper aims at getting an understanding of current problems and challenges with roadmapping processes in companies that are facing volatile markets with innovative products. It also aims at gathering ideas and attempts on how to react to those challenges.
Method: As an initial step towards the objectice a semi-structured expert interview study with a case company in the Smart Home domain was conducted. Four employees from the case company with different roles around product roadmaps have been interviewed and a content analysis of the data has been performed.
Results: The study shows a significant consensus among the interviewees about several major challenges and the necessity to change the traditional roadmapping process and format. The interviewees stated that based on their experience traditional feature-based product roadmaps are increasingly losing their benefits (such as good planning certainty) in volatile environments. Furthermore, the ability to understand customer needs and behaviors has become highly important for creating and adjusting product roadmaps. The interviewees see the need for both, sufficiently stable goals on the roadmap and flexibility with respect to products or features to be developed. To reach this target the interviewees proposed to create roadmaps based on outcome goals instead of product features. In addition, it was proposed to decrease the level of detail of the roadmaps and to emphasize the long-term view. Decisions about which feature to develop should be open as long as possible. Expected benefits of such a new way of product roadmapping are higher user centricity, a stable overall direction, more flexibility with respect to development decisions, and less breaking of commitments.
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.
Transforming our food system is important to achieving global climate neutrality and food security. Germany has set a national target of reaching a 30% share in organic farming to support the goal. When looking at the transformation process from conventional to organic farming, it becomes apparent that measures need to be taken to reach this anticipated goal. A particular emphasis of this work is placed on finding a digital solution and process improvements to ensure longevity and efficiency. Interviews with actors along the farm-to-fork value chain were conducted to identify central barriers and drivers of organic transformation. The results of the interviews show firstly, that three subsystems need to be distinguished when talking about the farm-to-fork value chain: (1) farmers, (2) intermediaries, and (3) the canteen system. Although all three subsystems can be combined to form a coherent value chain, they rarely act and communicate beyond the boundaries of their subsystem. Secondly, we were able to allocate primary barriers and drivers to each of the subsystems, highlighting the need to include all three in the transformation process and aim for a comprehensive digital solution. This work explores the potential of a network-based platform to improve the current practice of rigid and strictly hierarchical value chains. We focus on deriving user requirements from the interviews to describe the necessary functionality of the platform to address the identified barriers and exploit existing drivers.
Digital Enterprise Architecture allows multiple viewpoints on a company’s IT landscape. To gain valuable information out of huge amounts of operational data, it is indispensable to have both an understanding of the operations architecture and an engine capable of managing Big Data. The mechanism of understanding huge amounts of data is based on three main steps: collect, process and use. The main idea is focused on extracting valuable information out of Big Data to make better design decisions. The Elastic Stack is an open-source solution to comfortably and quickly handle Big Data scenarios.
Applications often need to be deployed in different variants due to different customer requirements. However, since modern applications often need to be deployed using multiple deployment technologies in combination, such as Ansible and Terraform, the deployment variability must be considered in a holistic way. To tackle this, we previously developed Variability4TOSCA and the prototype OpenTOSCA Vintner, which is a TOSCA preprocessing and management layer that implements Variability4TOSCA. In this demonstration, we present a detailed case study that shows how to model a deployment using Variability4TOSCA, how to resolve the variability using Vintner, and how the result can be deployed.
Digitization is the use of digital technologies for creating innovative digital business models and transforming existing business models, processes and systems. Digitization creates profound changes in the economy and society. Information is often captured and processed without human intervention using digital means. Digitization impacts nearly all products and services as well as the customer and the value-creation perspective.
The very first International Workshop on Software-intensive Business: Start-ups, Ecosystems and Platforms (SiBW 2018) was held in Espoo (Greater Helsinki), Finland on December 3rd, 2018 – just a day before SLUSH 2018, the world’s biggest startup event. Thanks to the collaboration with the organizers of SLUSH, many of the software-intensive business researchers and practitioners took part also in this event.
The international workshop gathered together 35 registered attendees, from Sweden, Germany, Latvia, Finland, Italy and the Netherlands representing both academia as well as industry. The event itself was sponsored by VTT Technical Research Centre of Finland and the workshop was organized by the newly founded Software-intensive Business research community together with Software Startup Research Network (SSRN).