探索持续改进和预测分析之间的关系

B. Galli, L. Ocampo
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引用次数: 0

摘要

本研究旨在探讨预测分析(PA)模型在持续改进(CI)领域的要素和应用。虽然数据科学、PA和大数据的作用已经在当前的文献中进行了探讨(例如,供应链管理),但很少有关于PA在CI计划中的作用的零散见解。有关PA和BI在CI项目中的作用的文章被用于系统的文献综述。此外,本文还强调了大数据分析在CI和PA决策过程中所起的重要作用。本文研究了与持续改进项目相关的其他重要CI和PA方面,这些方面在现有文献中经常被忽视。这项研究的结果强调了PA工具和概念在CI计划中可以而且应该发挥的关键作用。还需要实施关键的组织和操作结构,以便在CI计划中建立和维护PA工具和概念的使用。总的来说,本文填补了忽视这两个变量之间关系的空白。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the relationships between continuous improvement and predictive analytics
This study aimed to examine the elements and applications of predictive analytics (PA) models within the field of continuous improvement (CI). While the roles of data science, PA, and big data have been explored in the current literature (e.g., supply chain management), fragmented insights scarcely exist concerning the role of PA on CI initiatives. Articles concerning the role of PA and BI in CI projects were utilised in a systematic literature review. Furthermore, the paper stresses the vital role that big data analytics plays in both CI and PA during decision-making. The paper studies other important CI and PA aspects that pertain to continuous improvement projects, which are aspects that are often overlooked in the existing literature. The findings from this study emphasise the critical role that PA tools and concepts can and should have in CI initiatives. Critical organisational and operational structures also need to be implemented to establish and maintain the use of PA tools and concepts in CI initiatives. Overall, this paper serves to fill the gap that overlooks the relationship between these two variables.
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