Purpose

In recognising the key role of business intelligence and big data analytics in influencing companies’ decision-making processes, this paper aims to codify the main phases through which companies can approach, develop and manage big data analytics.

Design/methodology/approach

By adopting a research strategy based on case studies, this paper depicts the main phases and challenges that companies “live” through in approaching big data analytics as a way to support their decision-making processes. The analysis of case studies has been chosen as the main research method because it offers the possibility for different data sources to describe a phenomenon and subsequently to develop and test theories.

Findings

This paper provides a possible depiction of the main phases and challenges through which the approach(es) to big data analytics can emerge and evolve over time with reference to companies’ decision-making processes.

Research limitations/implications

This paper recalls the attention of researchers in defining clear patterns through which technology-based approaches should be developed. In its depiction of the main phases of the development of big data analytics in companies’ decision-making processes, this paper highlights the possible domains in which to define and renovate approaches to value. The proposed conceptual model derives from the adoption of an inductive approach. Despite its validity, it is discussed and questioned through multiple case studies. In addition, its generalisability requires further discussion and analysis in the light of alternative interpretative perspectives.

Practical implications

The reflections herein offer practitioners interested in company management the possibility to develop performance measurement tools that can evaluate how each phase can contribute to companies’ value creation processes.

Originality/value

This paper contributes to the ongoing debate about the role of digital technologies in influencing managerial and social models. This paper provides a conceptual model that is able to support both researchers and practitioners in understanding through which phases big data analytics can be approached and managed to enhance value processes.

中文翻译：

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在企业决策中管理大数据时超越技术主义

目的

认识到商业智能和大数据分析在影响公司决策过程中的关键作用，本文旨在整理公司处理、开发和管理大数据分析的主要阶段。

设计/方法/途径

通过采用基于案例研究的研究策略，本文描述了公司在将大数据分析作为支持其决策过程的一种方式时“经历”的主要阶段和挑战。案例研究分析已被选为主要的研究方法，因为它为不同的数据源提供了描述现象并随后发展和检验理论的可能性。

发现

本文提供了对主要阶段和挑战的可能描述，通过这些阶段和挑战，大数据分析方法可以参考公司的决策过程随着时间的推移出现和发展。

研究局限性/影响

本文回顾了研究人员在定义清晰模式时的注意力，通过这些模式应该开发基于技术的方法。在描述公司决策过程中大数据分析发展的主要阶段时，本文强调了定义和革新价值方法的可能领域。拟议的概念模型源于采用归纳法。尽管它是有效的，但通过多个案例研究对其进行了讨论和质疑。此外，它的普遍性需要根据不同的解释视角进行进一步的讨论和分析。

实际影响

本文的思考为对公司管理感兴趣的从业者提供了开发绩效衡量工具的可能性，这些工具可以评估每个阶段如何为公司的价值创造过程做出贡献。

原创性/价值

本文为关于数字技术在影响管理和社会模式方面的作用的持续辩论做出了贡献。本文提供了一个概念模型，能够支持研究人员和从业者理解通过哪些阶段可以接近和管理大数据分析以增强价值流程。