{"title":"适应不确定的和不断变化的企业需求:业务驱动的商业智能的案例","authors":"E. Yu, Alexei Lapouchnian, S. Deng","doi":"10.1109/RCIS.2013.6577687","DOIUrl":null,"url":null,"abstract":"Information systems today are expected to function in an increasingly dynamic world with many uncertainties. System development is seldom a linear progression from well-defined, fully-specified requirements to finished products that fully meet the initial requirements. More likely, there are ongoing cycles of exploration, design and implementation, taking into account evolving needs and capabilities, as well as lessons from earlier cycles. Existing requirements modeling and analysis techniques largely presume application settings that are stable and predictable. Can these techniques be used to support analysis in the new dynamic environment? Scenarios from the recent surge in demand for business intelligence capabilities in enterprises provide an interesting setting for examining organizational and IT responses to the challenges of high uncertainty and rapid change. In this paper, we apply existing requirements modeling techniques to these scenarios in order to uncover their inadequacies, and to identify research challenges.","PeriodicalId":167136,"journal":{"name":"IEEE 7th International Conference on Research Challenges in Information Science (RCIS)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Adapting to uncertain and evolving enterprise requirements: The case of business-driven business intelligence\",\"authors\":\"E. Yu, Alexei Lapouchnian, S. Deng\",\"doi\":\"10.1109/RCIS.2013.6577687\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Information systems today are expected to function in an increasingly dynamic world with many uncertainties. System development is seldom a linear progression from well-defined, fully-specified requirements to finished products that fully meet the initial requirements. More likely, there are ongoing cycles of exploration, design and implementation, taking into account evolving needs and capabilities, as well as lessons from earlier cycles. Existing requirements modeling and analysis techniques largely presume application settings that are stable and predictable. Can these techniques be used to support analysis in the new dynamic environment? Scenarios from the recent surge in demand for business intelligence capabilities in enterprises provide an interesting setting for examining organizational and IT responses to the challenges of high uncertainty and rapid change. In this paper, we apply existing requirements modeling techniques to these scenarios in order to uncover their inadequacies, and to identify research challenges.\",\"PeriodicalId\":167136,\"journal\":{\"name\":\"IEEE 7th International Conference on Research Challenges in Information Science (RCIS)\",\"volume\":\"147 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE 7th International Conference on Research Challenges in Information Science (RCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RCIS.2013.6577687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE 7th International Conference on Research Challenges in Information Science (RCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCIS.2013.6577687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adapting to uncertain and evolving enterprise requirements: The case of business-driven business intelligence
Information systems today are expected to function in an increasingly dynamic world with many uncertainties. System development is seldom a linear progression from well-defined, fully-specified requirements to finished products that fully meet the initial requirements. More likely, there are ongoing cycles of exploration, design and implementation, taking into account evolving needs and capabilities, as well as lessons from earlier cycles. Existing requirements modeling and analysis techniques largely presume application settings that are stable and predictable. Can these techniques be used to support analysis in the new dynamic environment? Scenarios from the recent surge in demand for business intelligence capabilities in enterprises provide an interesting setting for examining organizational and IT responses to the challenges of high uncertainty and rapid change. In this paper, we apply existing requirements modeling techniques to these scenarios in order to uncover their inadequacies, and to identify research challenges.