Organizational data strategy: Unveiling key elements and strategic types
基于75家企业的样本，开发了数据战略分类法，并通过聚类分析得出四种数据价值创造的战略类型，帮助决策者规划数据战略。
Organizations can use data in various ways to create business value. However, many firms struggle to use data as an integral part of their information systems (IS) and business strategies to innovate their business model and increase business value. As approaches for data-based value creation are still nascent or in development, conceptual work reflecting the diversity of data-based value-creation strategies within organizational settings is scarce. Based on a sample of 75 ventures, we develop a data strategy taxonomy to manifest the key characteristics of data-based strategy-making. We use the taxonomy and conduct a cluster analysis to derive four strategic types of data-based value creation: data for efficiency, data for complements, data for niche innovations, and data for attention and market control. Based on an evaluation of 12 firms where we conducted interviews, the four strategic types of data-based value creation provide a more thorough understanding of how organizations strategically integrate data into their business and IS strategy. The “data for attention and market control” strategic type extends classic findings on IS and business strategies arising from the pervasive market power and leadership position derived from data. As a practical implication, our results guide decision-makers to plan, communicate, and seize their data strategy ambitions.