{"date_created":"2022-10-13T07:51:09Z","user_id":"77201","citation":{"apa":"Meyer, M., Fichtler, T., Koldewey, C., &#38; Dumitrescu, R. (2022). How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning. <i> AMCIS 2022 Proceedings</i>. AMCIS 2022, Minneapolis.","mla":"Meyer, Maurice, et al. “How Can Data Analytics Results Be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning.” <i> AMCIS 2022 Proceedings</i>, 2022.","ama":"Meyer M, Fichtler T, Koldewey C, Dumitrescu R. How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning. In: <i> AMCIS 2022 Proceedings</i>. ; 2022.","ieee":"M. Meyer, T. Fichtler, C. Koldewey, and R. Dumitrescu, “How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning,” presented at the AMCIS 2022, Minneapolis, 2022.","chicago":"Meyer, Maurice, Timm Fichtler, Christian Koldewey, and Roman Dumitrescu. “How Can Data Analytics Results Be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning.” In <i> AMCIS 2022 Proceedings</i>. Minneapolis, 2022.","short":"M. Meyer, T. Fichtler, C. Koldewey, R. Dumitrescu, in:  AMCIS 2022 Proceedings, Minneapolis, 2022.","bibtex":"@inproceedings{Meyer_Fichtler_Koldewey_Dumitrescu_2022, place={Minneapolis}, title={How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning}, booktitle={ AMCIS 2022 Proceedings}, author={Meyer, Maurice and Fichtler, Timm and Koldewey, Christian and Dumitrescu, Roman}, year={2022} }"},"_id":"33708","title":"How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning","department":[{"_id":"563"}],"abstract":[{"text":"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.","lang":"eng"}],"author":[{"full_name":"Meyer, Maurice","id":"77201","last_name":"Meyer","first_name":"Maurice","orcid":"0000-0003-0606-7321"},{"full_name":"Fichtler, Timm","id":"66731","last_name":"Fichtler","first_name":"Timm"},{"full_name":"Koldewey, Christian","id":"43136","last_name":"Koldewey","first_name":"Christian","orcid":"https://orcid.org/0000-0001-7992-6399"},{"first_name":"Roman","full_name":"Dumitrescu, Roman","id":"16190","last_name":"Dumitrescu"}],"year":"2022","place":"Minneapolis","status":"public","type":"conference","date_updated":"2022-10-13T07:51:15Z","publication":" AMCIS 2022 Proceedings","conference":{"location":"Minneapolis","name":"AMCIS 2022"},"publication_status":"published","language":[{"iso":"eng"}]}