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Centralizing Data Management with Considerations of Uncertainty and Information-Based Flexibility

机译:集中考虑不确定性和基于信息的灵活性的数据管理

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This paper applies the theory of real options to analyze how the value of information-based flexibility should affect the decision to centralize or decentralize data management under low and high uncertainty. This study makes two main contributions. First, we show that in the presence of low uncertainty, centralization of data management decisions creates more total surplus for the firm as the similarity of business units increases. In contrast, in the presence of high uncertainty, centralization creates more total surplus as the dissimilarity of business units increases. The pivoting distinction trades the benefit of reduction of uncertainty from dissimilar businesses for centralization (with cost saving) against the benefit of flexibility from decentralization. Second, the framework helps senior management evaluate the trade-offs in data centralization that drive different business models of the firm. We illustrate the application of these propositions formally using an analytical model and informally using case vignettes and simulation.
机译:本文运用实物期权理论来分析基于信息的灵活性的价值应如何影响在低不确定性和高不确定性下集中或分散数据管理的决策。这项研究有两个主要贡献。首先,我们表明,在不确定性较低的情况下,随着业务部门相似性的提高,数据管理决策的集中化会为公司创造更多的总盈余。相反,在存在高度不确定性的情况下,随着业务部门之间差异的增加,集中化会产生更多的总盈余。关键的区分权衡了减少异类业务集中化(节省成本)带来的不确定性的好处与分散化带来的灵活性带来的好处。其次,该框架可帮助高级管理层评估驱动公司不同业务模式的数据集中化的权衡。我们使用解析模型来正式说明这些命题的应用,并使用案例短片和模拟来非正式地说明这些命题的应用。

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