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A fast way to test business ideas and to explore customer problems and needs is to talk to them. Customer interviews help to understand what solutions customers will pay for before investing valuable resources to develop solutions. Customer interviews are a good way to gain qualitative insights. However, conducting interviews can be a difficult procedure and requires specific skills. The current ways of teaching interview skills have significant deficiencies. They especially lack guidance and opportunities to practice. Objective: The goal of this work is to develop and validate a workshop format to teach interview skills for conducting good customer interviews in a practical manner. Method: The research method is based on design science research which serves as a framework. A game-based workshop format was designed to teach interview skills. The approach consists of a half-day, hands-on workshop and is based on an analysis of necessary interview skills. The approach has been validated in several workshops and improved based on learnings from those workshops. Results: Results of the validation show that participants could significantly improve their interview skills while enjoying the game-based exercises. The game-based learning approach supports learning and practicing customer interview skills with playful and interactive elements that encourage greater motivation among participants to conduct interviews.
Introducing continuous experimentation in large software-intensive product and service organisations
(2017)
Software development in highly dynamic environments imposes high risks to development organizations. One such risk is that the developed software may be of only little or no value to customers, wasting the invested development efforts.Continuous experiment ation, as an experiment-driven development approach, may reduce such development risks by iteratively testing product and service assumptions that are critical to the success of the software. Although several experiment-driven development approaches are available, there is little guidance available on how to introduce continuous experimentation into an organization. This article presents a multiple-case study that aims at better understanding the process of introducing continuous experimentation into an organization with an already established development process. The results from the study show that companies are open to adopting such an approach and learning throughout the introduction process. Several benefits were obtained, such as reduced development efforts, deeper customer insights, and better support for development decisions. Challenges included complex stakeholder structures, difficulties in defining success criteria, and building experimen- tation skills. Our findings indicate that organizational factors may limit the benefits of experimentation. Moreover, introducing continuous experimentation requires fundamental changes in how companies operate, and a systematic introduction process can increase the chances of a successful start.
Context: Companies need capabilities to evaluate the customer value of software intensive products and services. One way of systematically acquiring data on customer value is running continuous experiments as part of the overall development process. Objective: This paper investigates the first steps of transitioning towards continuous experimentation in a large company, including the challenges faced. Method: We conduct a single-case study using participant observation, interviews, and qualitative analysis of the collected data. Results: Results show that continuous experimentation was well received by the practitioners and practising experimentation helped them to enhance understanding of their product value and user needs. Although the complexities of a large multi-stakeholder business to-business (B2B) environment presented several challenges such as inaccessible users, it was possible to address impediments and integrate an experiment in an ongoing development project. Conclusion: Developing the capability for continuous experimentation in large organisations is a learning process which can be supported by a systematic introduction approach with the guidance of experts. We gained experience by introducing the approach on a small scale in a large organisation, and one of the major steps for future work is to understand how this can be scaled up to the whole development organisation.
Software Process Improvement (SPI) programs have been implemented, inter alia, to improve quality and speed of software development. SPI addresses many aspects ranging from individual developer skills to entire organizations. It comprises, for instance, the optimization of specific activities in the software lifecycle as well as the creation of organizational awareness and project culture. In the course of conducting a systematic mapping study on the state-of-the-art in SPI from a general perspective, we observed Software Quality Management (SQM) being of certain relevance in SPI programs. In this paper, we provide a detailed investigation of those papers from the overall systematic mapping study that were classified as addressing SPI in the context of SQM (including testing). From the main study’s result set, 92 papers were selected for an in-depth systematic review to study the contributions and to develop an initial picture of how these topics are addressed in SPI. Our findings show a fairly pragmatic contribution set in which different solutions are proposed, discussed, and evaluated. Among others, our findings indicate a certain reluctance towards standard quality or (test) maturity models and a strong focus on custom review, testing, and documentation techniques, whereas a set of five selected improvement measures is almost equally addressed.
Context: The manufacturing industry is facing a transformation with regard to Industry 4.0 (I4). A transformation towards full automation of production including a multitude of innovations is necessary. Startups and entrepreneurial processes can support such a transformation as has been shown in other industries. However, I4 has some specifics, so it is unclear how entrepreneurship can be adapted in I4. Understanding these specifics is important to develop suitable training programs for I4 startups and to accelerate the transformation.
Objective: This study identifies and outlines the essential characteristics and constraints of entrepreneurial processes in I4.
Method: 14 semi-structured interviews were conducted with experts in the field of I4 entrepreneurship. The interviews were analysed and categorized by qualitative analyses.
Results: The interviews revealed several characteristics of I4 that have a significant impact on the various phases of the entrepreneurial process. Examples of such specifics include the difficult access to customers, the necessary deep understanding of the customer and the domain, the difficulty of testing risky assumptions, and the complex development and productization of solutions. The complexity of hardware and software components, cost structures, and necessary customer-specific customizations affect the scalability of I4 startups. These essential characteristics also require specialised skills and resources from I4 startups.
Turning students into Industry 4.0 entrepreneurs: design and evaluation of a tailored study program
(2022)
Startups in the field of Industry 4.0 could be a huge driver of innovation for many industry sectors such as manufacturing. However, there is a lack of education programs to ensure a sufficient number of well-trained founders and thus a supply of such startups. Therefore, this study presents the design, implementation, and evaluation of a university course tailored to the characteristics of Industry 4.0 entrepreneurship. Educational design-based research was applied with a focus on content and teaching concept. The study program was first implemented in 2021 at a German university of applied sciences with 25 students, of which 22 participated in the evaluation. The evaluation of the study program was conducted with a pretest–posttest-design targeting three areas: (1) knowledge about the application domain, (2) entrepreneurial intention and (3) psychological characteristics. The entrepreneurial intention was measured based on the theory of planned behavior. For measuring psychological characteristics, personality traits associated with entrepreneurship were used. Considering the study context and the limited external validity of the study, the following can be identified in particular: The results show that a university course can improve participants' knowledge of this particular area. In addition, perceived behavioral control of starting an Industry 4.0 startup was enhanced. However, the results showed no significant effects on psychological characteristics.
Product roadmaps in the new mobility domain: state of the practice and industrial experiences
(2021)
Context: The New Mobility industry is a young market that includes high market dynamics and is therefore associated with a high degree of uncertainty. Traditional product roadmapping approaches such a detailed planning of features over a long-time horizon typically fail in such environments. For this reason, companies that are active in the field of New Mobility are faced with the challenge of keeping their product roadmaps reliable for stakeholders while at the same time being able to react flexibly to changing market requirements.
Objective: The goal of this paper is to identify the state of practice regarding product roadmapping of New Mobility companies. In addition, the related challenges within the product roadmapping process as well as the success factors to overcome these challenges will be highlighted.
Method: We conducted semi-structured expert interviews with 8 experts (7 German company and one Finnish company) from the field of New Mobility and performed a content analysis.
Results: Overall the results of the study showed that the participating companies are aware of the requirements that the New Mobility sector entails. Therefore, they exhibit a high level of maturity in terms of product roadmapping. Nevertheless, some aspects were revealed that pose specific challenges for the participating companies. One major challenge, for example, is that New Mobility in terms of public clients is often a tender business with non-negotiable product requirements. Thus, the product roadmap can be significantly influenced from the outside. As factors for a successful product roadmapping mainly soft factors such as trust between all people involved in the product development process and transparency throughout the entire roadmapping process were mentioned.
In the era of digital transformation, the notion of software quality transcends its traditional boundaries, necessitating an expansion to encompass the realms of value creation for customers and the business. Merely optimizing technical aspects of software quality can result in diminishing returns. Product discovery techniques can be seen as a powerful mechanism for crafting products that align with an expanded concept of quality - one that incorporates value creation. Previous research has shown that companies struggle to determine appropriate product discovery techniques for generating, validating, and prioritizing ideas for new products or features to ensure they meet the needs and desires of the customers and the business. For this reason, we conducted a grey literature review to identify various techniques for product discovery. First, the article provides an overview of different techniques and assesses how frequently they are mentioned in the literature review. Second, we mapped these techniques to an existing product discovery process from previous research to provide concrete guidelines for establishing product discovery in their organizations. The analysis shows, among other things, the increasing importance of techniques to structure the problem exploration process and the product strategy process. The results are interpreted regarding the importance of the techniques to practical applications and recognizable trends.
Providing a digital infrastructure, platform technologies foster interfirm collaboration between loosely coupled companies, enabling the formation of ecosystems and building the organizational structure for value co-creation. Despite the known potential, the development of platform ecosystems creates new sources of complexity and uncertainty due to the involvement of various independent actors. For a platform ecosystem to succeed, it is essential that the platform ecosystem participants are aligned, coordinated, and given a common direction. Traditionally, product roadmaps have served these purposes during product development. A systematic mapping study was conducted to better understand how product roadmapping could be used in the dynamic environment of platform ecosystems. One result of the study is that there are hardly any concrete approaches for product roadmapping in platform ecosystems so far. However, many challenges on the topic are described in the literature from different perspectives. Based on the results of the systematic mapping study, a research agenda for product roadmapping in platform ecosystems is derived and presented.
Today, companies face increasing market dynamics, rapidly evolving technologies, and rapid changes in customer behavior. Traditional approaches to product development typically fail in such environments and require companies to transform their often feature-driven mindset into a product-led mindset. A promising first step on the way to a product-led company is a better understanding of how product planning can be adapted to the requirements of an increasingly dynamic and uncertain market environment in the sense of product roadmapping. The authors developed the DEEP product roadmap assessment tool to help companies evaluate their current product roadmap practices and identify appropriate actions to transition to a more product-led company. Objective: The goal of this paper is to gain insight into the applicability and usefulness of version 1.1 of the DEEP model. In addition, the benefits, and implications of using the DEEP model in corporate contexts will be explored. Method: We conducted a multiple case study in which participants were observed using the DEEP model. We then interviewed each participant to understand their perceptions of the DEEP model. In addition, we conducted interviews with each company's product management department to learn how the application of the DEEP model influenced their attitudes toward product roadmapping. Results: The study showed that by applying the DEEP model, participants better understood which artifacts and methods were critical to product roadmapping success in a dynamic and uncertain market environment. In addition, the application of the DEEP model helped convince management and other stakeholders of the need to change current product roadmapping practices. The application also proved to be a suitable starting point for the transformation in the participating companies.