杠杆(统计)
分析
定性性质
背景(考古学)
数据科学
知识管理
产品设计
计算机科学
过程管理
产品(数学)
业务
几何学
数学
生物
机器学习
古生物学
作者
Can Azkan,Frederik Möller,Lennart Iggena,Boris Otto
标识
DOI:10.1109/tem.2022.3167737
摘要
The continuously growing availability and volume of data pressure companies to leverage them economically. Subsequently, companies must find strategies to incorporate data sensibly for internal optimization and find new business opportunities in data-driven business models. In this article, we focus on using data and data analytics in product-oriented industrial companies. Although data-driven services are becoming increasingly important, little is known about their systematic design and development in research. Surprisingly, many companies face significant challenges and fail to create these services successfully. Against this background, this article presents findings from a multicase based on qualitative interviews and workshops with experts from different industrial sectors. We propose ten design principles and corresponding design features to successfully design industrial data-driven services in this context. These design principles help practitioners and researchers to understand the peculiarities of creating data-driven services more in-depth on a conceptual, technical, and organizational level.
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