Impact of data analytics in transforming the decision-making process

Arthur Paul Christenson Jr., William Shalom Goldstein
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Abstract

Although business analytics is becoming more and more used to provide data-driven insights to support decision making, there is little research on how business analytics may be used at an organizational level to enhance decision making effectiveness. This paper develops a study model linking company analytics to organizational decision-making effectiveness, using the info processing view as well as contingency theory. Based on 740 responses from UK business organizations, the research model is examined using structural situation modelling. Key findings show that business analytics can be done through key findings. Mediating a data driven environment positively affects information processing abilities, which have a good impact on decision-making effectiveness in turn. The findings also show that the pathways from company analytics to decision making are obvious. There are no statistical differences between large and small businesses, but several differences between the manufacturing and professional services industries. Our findings add to the literature on business analytics by offering helpful insights into company analytics applications and the facilitation of data driven decision making. They also improve the knowledge and understanding of managers by showing how business analytics needs to be applied to improve decision making effectiveness.
数据分析在改变决策过程中的影响
尽管业务分析越来越多地用于提供数据驱动的见解来支持决策,但关于如何在组织层面上使用业务分析来提高决策效率的研究却很少。本文运用信息处理理论和权变理论,建立了公司分析与组织决策有效性的研究模型。基于来自英国商业组织的740份回复,研究模型使用结构情境模型进行了检验。关键发现表明,业务分析可以通过关键发现来完成。中介数据驱动环境正向影响信息处理能力,信息处理能力反过来对决策有效性产生良好影响。研究结果还表明,从公司分析到决策的途径是显而易见的。大企业和小企业之间没有统计差异,但制造业和专业服务业之间存在一些差异。我们的研究结果通过为公司分析应用和促进数据驱动决策提供有用的见解,增加了商业分析的文献。他们还通过展示如何应用业务分析来提高决策效率,提高了管理人员的知识和理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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