@inproceedings{63652, abstract = {{In dynamic environments, product management plays a key role in aligning innovation, customer needs, and strategic decision-making. Digitalization offers significant opportunities to enhance this role by enabling data-driven insights for improved customer and product understanding—yet its successful implementation requires a fundamental transformation. Based on a systematic literature review, this study synthesizes key advantages, challenges, and design fields that shape this transformation. The results highlight performance benefits across business, product, process, and decision-making dimensions, while also uncovering barriers rooted in strategy, organization, people, and technology. To address these barriers, critical enablers and conditions for success are identified. Four overarching design fields provide orientation for structuring digitalization efforts and guiding organizational change in industrial practice. The paper provides both a conceptual foundation and a practical guide for companies seeking to digitalize their product management effectively.}}, author = {{Fichtler, Timm and Petzke, Lisa Irene and Grigoryan, Khoren and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{Proceedings of the 59th Hawaii International Conference on System Sciences}}, location = {{Maui, Hawaii}}, title = {{{Enhancing Product Management Performance through Digitalization: Advantages, Challenges, Design Fields}}}, year = {{2026}}, } @techreport{63650, author = {{Kaufmann, Jonas and Schreiner, Nick and Koldewey, Christian and Fichtler, Timm and Sommer, Franziska and Sedlmeier, Joachim and Hocken, Christian and Rabe, Martin and Kühn, Arno}}, title = {{{Breaking Barriers: Implementing IoT-enabled Smart Services for Competitive Advantage}}}, doi = {{10.13140/RG.2.2.19531.50723}}, year = {{2025}}, } @techreport{63651, author = {{Grigoryan, Khoren and Lamarz, Jessica and Martin, Lucas and Asmar, Laban and Rabe, Martin and Kühn, Arno and Fichtler, Timm and Petzke, Lisa Irene and Bruchhage, Felix and Koldewey, Christian}}, title = {{{product.intelligence - Datenbasiertes Produktmanagement}}}, doi = {{10.24406/PUBLICA-4198}}, year = {{2025}}, } @inproceedings{59222, author = {{Grigoryan, Khoren and Martin, Lucas and Fichtler, Timm and Reinhold, Jannik and Asmar, Laban and Kühn, Arno and Dumitrescu, Roman}}, booktitle = {{Vorausschau und Technologieplanung - 18. Symposium für Vorausschau und Technologieplanung}}, editor = {{Dumitrescu, Roman and Hölzle, Katharina}}, location = {{Berlin}}, publisher = {{Verlagsschriftenreihe des Heinz Nixdorf Instituts}}, title = {{{Leitfaden zur Planung von Datenanalysen zur Entscheidungsunterstützung im Produktmanagement}}}, year = {{2025}}, } @inproceedings{61955, author = {{Koldewey, Christian and Rohde, Malte Nick and Strobel, Gero and Vehmeyer, Julia Marie and Fichtler, Timm and Dumitrescu, Roman}}, booktitle = {{2025 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC)}}, publisher = {{IEEE}}, title = {{{Embedding Generative AI into Products – 10 Design Principles for Building Intelligent Systems}}}, doi = {{10.1109/ice/itmc65658.2025.11106522}}, year = {{2025}}, } @inproceedings{61954, author = {{Fichtler, Timm and Petzke, Lisa Irene and Grigoryan, Khoren and Dumitrescu, Roman and Koldewey, Christian}}, booktitle = {{2025 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC)}}, publisher = {{IEEE}}, title = {{{Digital Transformation of Organizational Entities}}}, doi = {{10.1109/ice/itmc65658.2025.11106627}}, year = {{2025}}, } @inproceedings{61973, author = {{Grigoryan, Khoren and Martin, Lucas and Lamarz, Jessica and Fichtler, Timm and Hohn, Bennett and Asmar, Laban and Kühn, Arno and Dumitrescu, Roman}}, booktitle = {{Procedia CIRP}}, issn = {{2212-8271}}, pages = {{838--843}}, publisher = {{Elsevier BV}}, title = {{{Product Management: Tasks, Roles, and the Importance of Data}}}, doi = {{10.1016/j.procir.2025.08.143}}, volume = {{136}}, year = {{2025}}, } @inproceedings{61971, author = {{Fichtler, Timm and Petzke, Lisa Irene and Grigoryan, Khoren and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{Procedia CIRP}}, issn = {{2212-8271}}, pages = {{985--990}}, publisher = {{Elsevier BV}}, title = {{{Success Factors in Product Management and the Role of Data}}}, doi = {{10.1016/j.procir.2025.08.167}}, volume = {{136}}, year = {{2025}}, } @inproceedings{61953, author = {{Grigoryan, Khoren and Bauer, Eliana and Fichtler, Timm and Asmar, Laban and Kühn, Arno and Dumitrescu, Roman}}, booktitle = {{2025 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC)}}, publisher = {{IEEE}}, title = {{{A Structured Tool Landscape for Data-Driven ProductManagernent}}}, doi = {{10.1109/ice/itmc65658.2025.11106543}}, year = {{2025}}, } @inproceedings{48632, abstract = {{Digital Servitization is one of the significant trends affecting the manufacturing industry. Companies try to tackle challenges regarding their differentiation and profitability using digital services. One specific type of digital services are smart services, which are digital services built on data from smart products. Introducing these kinds of offerings into the portfolio of manufacturing companies is not trivial. Moreover, they require conscious action to align all relevant capabilities to realize the respective business goals. However, what capabilities are generally relevant for smart services remains opaque. We conducted a systematic literature review to identify them and extended the results through an interview study. Our analysis results in 78 capabilities clustered among 12 principles and six dimensions. These results provide significant support for the smart service transformation of manufacturing companies and for structuring the research field of smart services.}}, author = {{Koldewey, Christian and Fichtler, Timm and Scholtysik, Michel and Biehler, Jan and Schreiner, Nick and Sommer, Franziska and Schacht, Maximilian and Kaufmann, Jonas and Rabe, Martin and Sedlmeier, Joachim and Dumitrescu, Roman}}, keywords = {{Digital Servitization, Transformation, Capabilities, Maturity, Smart Services}}, location = {{Hawaii}}, title = {{{Exploring Capabilities for the Smart Service Transformation in Manufacturing: Insights from Theory and Practice}}}, year = {{2024}}, } @inproceedings{56170, author = {{Grigoryan, Khoren and Fichtler, Timm and Asmar, Laban and Kühn, Arno and Dumitrescu, Roman}}, booktitle = {{AMCIS 2024 Proceedings}}, title = {{{63 Use Cases for Analyzing Data in Product Management of Manufacturing Companies}}}, year = {{2024}}, } @inproceedings{55186, author = {{Fichtler, Timm and Petzke, Lisa Irene and Grigoryan, Khoren and Koldewey, C. and Dumitrescu, Roman}}, booktitle = {{Procedia CIRP}}, issn = {{2212-8271}}, pages = {{539--544}}, publisher = {{Elsevier BV}}, title = {{{A Method for Identifying Use Cases in Data-Driven Product Management}}}, doi = {{10.1016/j.procir.2024.01.079}}, volume = {{122}}, year = {{2024}}, } @inproceedings{55185, author = {{Fichtler, Timm and Grigoryan, Khoren and Petzke, Lisa Irene and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{PACIS 2024 Proceedings}}, location = {{Ho Chi Minh City}}, title = {{{Application Areas and Challenges of Data-Driven Product Management}}}, year = {{2024}}, } @inproceedings{59221, author = {{Fichtler, Timm and Petzke, Lisa Irene and Grigoryan, Khoren and Koldewey, C. and Dumitrescu, Roman}}, booktitle = {{2024 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}}, publisher = {{IEEE}}, title = {{{Antecedents of Data-Driven Product Management – Data Taxonomy and Cluster & Software Categories}}}, doi = {{10.1109/ictmod63116.2024.10878154}}, year = {{2024}}, } @inproceedings{52369, abstract = {{Megatrends, such as digitization or sustainability, are confronting the product management of manufacturing companies with a variety of challenges regarding the design of future products, but also the management of the actual products. To successfully position their products in the market, product managers need to gather and analyze comprehensive information about customers, developments in the products’ environment, product usage, and more. The digitization of all aspects of life is making data on these topics increasingly available – via social media, documents, or the internet of things from the products themselves. The systematic collection and analysis of these data enable the exploitation of new potentials for the adaption of existing products and the creation of the products of tomorrow. However, there are still no insights into the main concepts and cause-effect relationships in exploiting data-driven approaches for product management. Therefore, this paper aims to identify the main concepts and advantages of data-driven product management. To answer the corresponding research questions a comprehensive systematic literature review is conducted. From its results, a detailed description of the main concepts of data-driven product management is derived. Furthermore, a taxonomy for the advantages of data-driven product management is presented. The main concepts and the taxonomy allow for a deeper understanding of the topic while highlighting necessary future actions and research needs.}}, author = {{Fichtler, Timm and Grigoryan, Khoren and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}}, keywords = {{Product Lifecyle Management (PLM), Data Analytics, Data-driven Design, Engineering Management, Lifecycle Data}}, location = {{Rabat, Morocco}}, publisher = {{IEEE}}, title = {{{Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research}}}, doi = {{10.1109/ictmod59086.2023.10438135}}, year = {{2023}}, } @techreport{53554, author = {{Dumitrescu, Roman and Riemensperger, Frank and Schuh, Günther and Biehler, Jan and Frey, Anna and Hocken, Christian and Koldewey, Christian and Kühn, Arno and Rabe, Martin and Schacht, Maximilian and Comans, Sebastian and Fichtler, Timm and Govioni, Alina and Harland, Tobias and Kaufmann, Jonas and Optehostert, Felix and Rieger, Marcel and Scholtysik, Michel and Schreiner, Nick and Sedlmeir, Joachim and Sommer, Franziska}}, title = {{{acatech Maturity Index Smart Services}}}, year = {{2023}}, } @inproceedings{45793, abstract = {{The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.}}, author = {{Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}}, booktitle = {{Procedia CIRP 33}}, keywords = {{Product Management, Data Analytics, Data-Driven Design, Product-related data, Lifecycle Data, Tool-support}}, location = {{Sydney}}, title = {{{Data-Driven Product Management: A Practitioner-Driven Research Agenda}}}, year = {{2023}}, } @inproceedings{45812, author = {{Özcan, Leon and Fichtler, Timm and Kasten, Benjamin and Koldewey, Christian and Dumitrescu, Roman}}, keywords = {{Digital Platform, Platform Strategy, Strategic Management, Platform Life Cycle, Interview Study, Business Model, Business-to-Business, Two-sided Market, Multi-sided Market}}, location = {{Ljubljana}}, title = {{{Interview Study on Strategy Options for Platform Operation in B2B Markets}}}, year = {{2023}}, } @inproceedings{33708, abstract = {{The megatrend digitalization turns mechatronic products into continuous collectors and generators of use phase data. By analyzing this data, manufacturers can uncover valuable insights about the products and the users. Especially in product planning, these insights could be used to plan promising future product generations. The systematic exploitation of data analytics results, however, represents a serious challenge, as research on the topic is still scarce. In this paper, we present 13 design principles for exploiting data analytics results in product planning. The results are based on a systematic literature review and a workshop with a research consortium. The evaluation of the design principles is demonstrated with a real case of a manufacturing company. The identified design principles represent a first contribution to a still scarcely explored research field.}}, author = {{Meyer, Maurice and Fichtler, Timm and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{ AMCIS 2022 Proceedings}}, location = {{Minneapolis}}, title = {{{How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning}}}, year = {{2022}}, } @article{30193, abstract = {{The successful planning of future product generations requires reliable insights into the actual products’ problems and potentials for improvement. A valuable source for these insights is the product use phase. In practice, product planners are often forced to work with assumptions and speculations as insights from the use phase are insufficiently identified and documented. A new opportunity to address this problem arises from the ongoing digitalization that enables products to generate and collect data during their utilization. Analyzing these data could enable their manufacturers to generate and exploit insights concerning product performance and user behavior, revealing problems and potentials for improvement. However, research on analyzing use phase data in product planning of manufacturing companies is scarce. Therefore, we conducted an exploratory interview study with decision-makers of eight manufacturing companies. The result of this paper is a detailed description of the potentials and challenges that the interviewees associated with analyzing use phase data in product planning. The potentials explain the intended purpose and generic application examples. The challenges concern the products, the data, the customers, the implementation, and the employees. By gathering the potentials and challenges through expert interviews, our study structures the topic from the perspective of the potential users and shows the needs for future research.}}, author = {{Meyer, Maurice and Fichtler, Timm and Koldewey, Christian and Dumitrescu, Roman}}, issn = {{0890-0604}}, journal = {{Artificial Intelligence for Engineering Design, Analysis and Manufacturing}}, keywords = {{Artificial Intelligence, Industrial and Manufacturing Engineering}}, publisher = {{Cambridge University Press (CUP)}}, title = {{{Potentials and challenges of analyzing use phase data in product planning of manufacturing companies}}}, doi = {{10.1017/s0890060421000408}}, volume = {{36}}, year = {{2022}}, }