{"title":"建立共同的数据驱动文化:对大型公共部门机构在数据驱动过程中出现的紧张局势和新解决方案的纵向研究","authors":"","doi":"10.1016/j.jss.2024.112185","DOIUrl":null,"url":null,"abstract":"<div><p>In recent years, the push to make organizations data-driven has led to data-focused software projects, both in the private and public sectors. The strive for increasing data-driven initiatives introduces a range of new socio-technical challenges, yet there are to date few empirical studies in terms of how data-focused initiatives affect large organizations with significant variations in terms of data needs and usage. This study presents a longitudinal descriptive case study of how data-driven initiatives in the Norwegian public sector cause organizational tensions in a very large, complex organization. We conducted 32 semi-structured interviews over a period of 18 months representing two different data-intensive parts of the organization that had developed incompatible data cultures. Our study shows that these cultural differences create organizational conflicts that hinder data-driven initiatives. The findings also suggest, however, that overcoming these is possible through the strategic, top-down facilitation of a common data-driven culture built on uniting data principles, in turn potentially leading to improved decision-making and enhanced innovation.</p></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards a common data-driven culture: A longitudinal study of the tensions and emerging solutions involved in becoming data-driven in a large public sector organization\",\"authors\":\"\",\"doi\":\"10.1016/j.jss.2024.112185\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In recent years, the push to make organizations data-driven has led to data-focused software projects, both in the private and public sectors. The strive for increasing data-driven initiatives introduces a range of new socio-technical challenges, yet there are to date few empirical studies in terms of how data-focused initiatives affect large organizations with significant variations in terms of data needs and usage. This study presents a longitudinal descriptive case study of how data-driven initiatives in the Norwegian public sector cause organizational tensions in a very large, complex organization. We conducted 32 semi-structured interviews over a period of 18 months representing two different data-intensive parts of the organization that had developed incompatible data cultures. Our study shows that these cultural differences create organizational conflicts that hinder data-driven initiatives. The findings also suggest, however, that overcoming these is possible through the strategic, top-down facilitation of a common data-driven culture built on uniting data principles, in turn potentially leading to improved decision-making and enhanced innovation.</p></div>\",\"PeriodicalId\":51099,\"journal\":{\"name\":\"Journal of Systems and Software\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Systems and Software\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0164121224002292\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Systems and Software","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0164121224002292","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Towards a common data-driven culture: A longitudinal study of the tensions and emerging solutions involved in becoming data-driven in a large public sector organization
In recent years, the push to make organizations data-driven has led to data-focused software projects, both in the private and public sectors. The strive for increasing data-driven initiatives introduces a range of new socio-technical challenges, yet there are to date few empirical studies in terms of how data-focused initiatives affect large organizations with significant variations in terms of data needs and usage. This study presents a longitudinal descriptive case study of how data-driven initiatives in the Norwegian public sector cause organizational tensions in a very large, complex organization. We conducted 32 semi-structured interviews over a period of 18 months representing two different data-intensive parts of the organization that had developed incompatible data cultures. Our study shows that these cultural differences create organizational conflicts that hinder data-driven initiatives. The findings also suggest, however, that overcoming these is possible through the strategic, top-down facilitation of a common data-driven culture built on uniting data principles, in turn potentially leading to improved decision-making and enhanced innovation.
期刊介绍:
The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to:
• Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution
• Agile, model-driven, service-oriented, open source and global software development
• Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems
• Human factors and management concerns of software development
• Data management and big data issues of software systems
• Metrics and evaluation, data mining of software development resources
• Business and economic aspects of software development processes
The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.