This paper examines how organizations create data-driven value propositions. Data-driven value propositions define what customer value is created based on data. We study the dynamics underlying this process in a European postal-service organization. We develop a model that shows that the process of creating data-driven value propositions is emergent, consisting of iterative resourcing cycles. We find that creating data-driven value propositions involves the performance of two types of resourcing actions: data reconstructing and data repurposing. The process is shaped by two types of data qualities: apparent qualities, i.e., qualities perceived ex-ante as potentially significant for creating value propositions; and latent qualities, which raise unforeseen consequences en route. We discuss the implications of these findings for the literature on creating data-driven value propositions, for our understanding of data as a strategic resource, and for the literature on resourcing.

本文研究了组织如何创建数据驱动的价值主张。数据驱动的价值主张定义了基于数据创造的客户价值。我们研究了欧洲邮政服务组织中这一过程背后的动态。我们开发了一个模型，该模型表明创建数据驱动的价值主张的过程是紧急的，由迭代资源循环组成。我们发现，创建数据驱动的价值主张涉及两种类型的资源配置行为的执行：数据重建和数据再利用。该过程由两种类型的数据质量决定： 表观质量，即事前被认为​​对创建价值主张具有潜在重要性的质量；和潜在的品质，这会在途中引发无法预料的后果。