图书情报知识 ›› 2021, Vol. 38 ›› Issue (4): 114-124.doi: 10.13366/j.dik.2021.04.114

• 知识、学习与管理 • 上一篇    下一篇

数据驱动的智库知识服务流程优化

申静,杨家鑫   

  • 出版日期:2021-07-10 发布日期:2021-08-29

Data-driven Process Optimization of Think Tanks’ Knowledge Service

  • Online:2021-07-10 Published:2021-08-29

摘要: [目的/意义]将数据驱动思想应用于智库的知识服务实践,优化智库的知识服务流程,提高智库的工作效率和服务水平。
[研究设计/方法] 结合文献回顾和网络调研分析智库知识服务流程及具体环节;针对存在的问题,引入大数据思维和大数据分析技术,采用标杆分析法对智库知识服务的具体环节进行优化,提出数据驱动的智库知识服务流程优化框架,并分析该框架应用的最佳实践。 [结论/发现] 服务流程优化后的智库可以同时开展数据驱动的精准型知识服务、主动型知识服务和客户自主型知识服务,这三类知识服务不仅可以提高智库的工作效率和服务水平,还能更好满足客户了解社会热点、应急决策和创新服务等多样化知识服务需求。[创新/价值]运用数据驱动思想,基于用户需求,引入大数据思维和大数据分析技术对智库的知识服务流程进行了系统优化,为大数据时代的智库知识服务实现数字化转型提供了参考。

关键词: 智库, 知识服务, 流程优化, 数据驱动, 大数据分析

Abstract: [Purpose/Significance]The application of data-driven thinking in think tanks could optimize its knowledge service process and improve work efficiency and service level.[Design/Methodology]Firstly, literature review and internet research were combined to analyze think tanks’ knowledge service process. Aiming at the existing problems, big data thinking and analysis technology were introduced. Meanwhile, benchmarking analysis was adopted to optimize the concrete procedures, and the data-driven process optimization framework was proposed for think tanks’ knowledge service. Additionally, best practice of the framework application was analyzed.[Findings/Conclusion]Think tanks with optimized service process can produce accurate knowledge service, active knowledge service and customer self-initiative knowledge service, which are all data-driven. These three types of knowledge services will not only improve think tanks’ work efficiency and service level, but also better meet customers’ diverse needs such as knowing hot social issues, making decisions in emergencies and innovating services.[Originality/Value]The process of think tanks’ knowledge service has been systematically optimized by adopting big data thinking and big data analyzing technology, which is based on data-driven thoughts and users’ needs. It could provide references for realizing digital transformation of think tanks’ knowledge services in the era of big data.

Keywords: Think tank, Knowledge service, Process optimization, Data-driven, Big data analysis