Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework

Jia Xu, Humza Naseer, S. Maynard, Justin Filippou
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Abstract

Organisations are increasingly practising business analytics to generate actionable insights that can guide their digital business transformation. Transforming business digitally using business analytics is an ongoing process that requires an integrated and disciplined approach to leveraging analytics and promoting collaboration. An emerging business analytics practice, Data Operations (DataOps), provides a disciplined approach for organisations to collaborate using analytical information for digital business transformation. We propose a conceptual framework by reviewing the literature on business analytics, DataOps and organisational information processing theory (OIPT). This conceptual framework explains how organisations can employ DataOps as an integrated and disciplined approach for developing the analytical information processing capability and facilitating boundary-spanning activities required for digital business transformation. This research (a) extends current knowledge on digital transformation by linking it with business analytics from the perspective of OIPT and boundary-spanning activities, and (b) presents DataOps as a novel approach for using analytical information for digital business transformation.
通过数据运营利用分析信息促进数字化业务转型:回顾与概念框架
企业正越来越多地采用商业分析方法来产生可操作的洞察力,以指导其数字化业务转型。利用业务分析进行数字化业务转型是一个持续的过程,需要采用综合、规范的方法来利用分析和促进协作。新兴的业务分析实践--数据运营(DataOps)为企业提供了一种规范的方法,使其能够利用分析信息进行协作,从而实现数字化业务转型。我们通过回顾有关商业分析、数据运营和组织信息处理理论(OIPT)的文献,提出了一个概念框架。这一概念框架解释了组织如何将数据运营作为一种综合、规范的方法来开发分析信息处理能力,并促进数字化业务转型所需的跨边界活动。本研究(a)从组织信息处理能力(OIPT)和跨界活动的角度,将数字化转型与业务分析联系起来,从而扩展了当前有关数字化转型的知识;(b)提出了数据运营(DataOps)这一利用分析信息促进数字化业务转型的新方法。
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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