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Success factors for implementing Business Analytics in small and medium enterprises in the food industry

机译:在食品工业中实施中小企业业务分析的成功因素

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In an increasingly changing market environment, the long-term survival of companies depends on their ability to reduce latencies in adapting to new market conditions. One strategy to meet this challenge is the anchoring of data-driven decision making, which leads to an increasing use of advanced information technologies and, subsequently, to an increase in the amount of data stored. The complexity of processing these data spurred the demand for advanced statistical methods and functions called Business Analytics. Companies are, despite all promised benefits, overwhelmed with the implementation of Business Analytics as indicated by a failure rate of 65 to 80 %. This paper provides an empirically validated, multi-dimensional model that takes an integrative look at critical success factors for the implementation of Business Analytics and based on which management recommendations can be generated. For this purpose, constructs of the model are conceptualized, before a structural equation model is developed. This model is then validated with data from 69 industrial partners in the food industry. It is shown amongst others, that the three success factors top management support, IT infrastructure and system quality are pivotal to increase the company performance.
机译:在越来越不断变化的市场环境中,公司的长期生存取决于他们减少适应新市场条件的延迟的能力。一个符合这一挑战的一个策略是数据驱动决策的锚定,这导致了越来越多地利用高级信息技术,随后增加了存储的数据量的增加。处理这些数据的复杂性促使了对经营分析的高级统计方法和功能的需求。尽管所有承诺的福利,但是在实施业务分析的情况下,公司的情况是,如失败率为65%至80%。本文提供了一个经验验证的多维模型,采用综合查看业务分析的关键成功因素,并基于可以生成的管理建议。为此目的,在开发结构方程模型之前,模型的构造是概念化的。然后将该模型验证了食品工业中的69个工业合作伙伴的数据。它在其他人之中显示,这三个成功因素最高管理支持,IT基础设施和系统质量是衡量公司的表现。

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