Integrating big data and cloud computing into the existing system and performance impact: A case study in manufacturing

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2024-11-16 DOI:10.1016/j.techfore.2024.123883

Jeetendra Kumar Saraswat, Sanjay Choudhari

{"title":"Integrating big data and cloud computing into the existing system and performance impact: A case study in manufacturing","authors":"Jeetendra Kumar Saraswat, Sanjay Choudhari","doi":"10.1016/j.techfore.2024.123883","DOIUrl":null,"url":null,"abstract":"<div><div>Manufacturing companies generate vast but underutilised business data in ERP systems. Valuable insights can be derived from unexplored data by using big data analytics, enabling managers to make well-informed decisions. Cloud computing, with its cost-effective resources, offers access to hosting and facilitating such access. Despite extensive literature, real-life applications illustrating how manufacturing companies can derive value from data through the integration of big data and cloud are still lacking.</div><div>This study, based on a manufacturing case study, investigates the process of integrating big data and cloud computing into the existing ERP system. It is argued in the literature that big data benefits will be limited if it is not aligned with the established culture and resources in the implementation process, known as big data capability. The paper explores the company's journey, evaluating the importance and overall development of preexisting capability during adoption. The work assesses the impact of big data on operational performance. The several insights obtained from the real-life case serve as a valuable guide for managers embarking on big data projects. The findings establish the importance of big data capability and illustrate how manufacturing companies can seamlessly integrate these technologies and improve performance without compromising existing ERP systems.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"210 ","pages":"Article 123883"},"PeriodicalIF":12.9000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technological Forecasting and Social Change","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040162524006814","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}

引用次数: 0

Abstract

Manufacturing companies generate vast but underutilised business data in ERP systems. Valuable insights can be derived from unexplored data by using big data analytics, enabling managers to make well-informed decisions. Cloud computing, with its cost-effective resources, offers access to hosting and facilitating such access. Despite extensive literature, real-life applications illustrating how manufacturing companies can derive value from data through the integration of big data and cloud are still lacking.

This study, based on a manufacturing case study, investigates the process of integrating big data and cloud computing into the existing ERP system. It is argued in the literature that big data benefits will be limited if it is not aligned with the established culture and resources in the implementation process, known as big data capability. The paper explores the company's journey, evaluating the importance and overall development of preexisting capability during adoption. The work assesses the impact of big data on operational performance. The several insights obtained from the real-life case serve as a valuable guide for managers embarking on big data projects. The findings establish the importance of big data capability and illustrate how manufacturing companies can seamlessly integrate these technologies and improve performance without compromising existing ERP systems.

查看原文本刊更多论文

将大数据和云计算融入现有系统及其性能影响：制造业案例研究

制造企业在 ERP 系统中生成了大量业务数据，但这些数据却未得到充分利用。通过使用大数据分析，可以从未曾开发的数据中获得有价值的见解，使管理人员能够做出明智的决策。云计算具有成本效益高的资源，可提供托管服务并促进这种访问。本研究以一个制造业案例为基础，探讨了将大数据和云计算整合到现有 ERP 系统的过程。有文献认为，在实施过程中，如果大数据与既定的文化和资源（即大数据能力）不相匹配，那么大数据的效益将是有限的。本文探讨了公司的发展历程，评估了在采用过程中已有能力的重要性和整体发展情况。作品评估了大数据对运营绩效的影响。从真实案例中获得的若干启示，可为着手开展大数据项目的管理人员提供宝贵的指导。研究结果确定了大数据能力的重要性，并说明了制造企业如何在不影响现有 ERP 系统的情况下无缝集成这些技术并提高绩效。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

期刊介绍： Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.