Purpose

Business analytics (BA) has been a breakthrough technological development in recent years. Although scholars have suggested several solutions in using these technologies to facilitate decision-making, there are as of yet limited studies on how analysts, in practice, improve decision makers' understanding of business environments. This study uses sensemaking theory and proposes a model of how data analysts generate analytical outcomes to improve decision makers' understanding of the business environment.

Design/methodology/approach

This study employs an interpretive field study with thematic analysis. The authors conducted 32 interviews with data analysts and consultants in Australia and New Zealand. The authors then applied thematic analysis to the collected data.

Findings

The thematic analysis discovered four main sensegiving activities, including data integration, trustworthiness analysis, appropriateness analysis and alternative selection. The proposed model demonstrates how these activities support the properties of sensemaking and result in improved decision-making.

Research limitations/implications

This study provides strong empirical evidence for the theory development and practice of sensemaking. It brings together two distinct fields – sensemaking and business analytics – and demonstrates how the approaches advocated by these two fields could improve analytics applications. The findings also propose theoretical implications for information system development (ISD).

Practical implications

This study demonstrates how data analysts could use analytical tools and social mechanisms to improve decision makers' understanding of the business environment.

Originality/value

This study is the first known empirical study to conceptualize the theory of sensemaking in the context of BA and propose a model for analytical sensegiving in organizations.

中文翻译：

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通过使用业务分析在组织中进行感知

目的

近年来，业务分析 (BA) 一直是一项突破性的技术发展。尽管学者们提出了几种使用这些技术来促进决策的解决方案，但目前关于分析师如何在实践中提高决策者对商业环境的理解的研究还很有限。本研究使用意义建构理论，并提出了一个模型，说明数据分析师如何生成分析结果以提高决策者对商业环境的理解。

设计/方法/方法

本研究采用带有主题分析的解释性实地研究。作者对澳大利亚和新西兰的数据分析师和顾问进行了 32 次采访。然后，作者对收集到的数据进行了专题分析。

发现

主题分析发现了四种主要的意义活动，包括数据整合、可信度分析、适当性分析和替代选择。所提出的模型展示了这些活动如何支持意义构建的特性并导致决策的改进。

研究限制/影响

本研究为意义建构的理论发展和实践提供了强有力的经验证据。它汇集了两个不同的领域——意义构建和业务分析——并展示了这两个领域提倡的方法如何改进分析应用程序。研究结果还提出了对信息系统开发 (ISD) 的理论意义。

实际影响

本研究展示了数据分析师如何使用分析工具和社会机制来提高决策者对商业环境的理解。

原创性/价值

这项研究是第一个已知的实证研究，将 BA 背景下的意义建构理论概念化，并提出了一个组织中分析意义的模型。