摘要
以商业智能(Business Intelligence)为代表的数据分析已在运营管理、市场营销以及财务金融领域取得了丰硕成果,但人力资源部门依然处于数据分析的初始阶段,其管理职能的实现主要建立在经验和直觉的基础上。数据爆炸和大数据技术的兴起彻底改变了商业分析的面貌,也为人力资源部门向数据驱动转型提供了前所未有的战略机遇。在人才的重要性日益凸显、企业间人才竞争加剧的形势下,利用大数据技术重塑人力分析和人力资源管理成为人力资源部门应对挑战、支撑企业长期竞争优势的关键。文章尝试从人力分析(数据搜集、数据整合和清理、数据分析、数据洞见的呈现)、人力资源管理部门(规划、招聘、绩效、留任、员工问题)和组织(人力资源部门的角色、组织架构、组织文化)三个层面建立大数据人力资源管理的理论框架,系统阐述大数据技术给人力资源管理带来的变革和挑战,并从学科交叉的角度解释其内在逻辑,探讨了大数据人力资源领域将来的研究方向。
Starting with Frederick Winslow Taylor, the founder of modern management, managers have been committed to making management based on quantitative analysis. As Peter Drucker said,＂If you cannot measure,you cannot manage. ＂ Today, Business Intelligence has yielded brilliant achievements in operations management,marketing,and finance. But HR department is still on the initial stage of data analysis,and its function is still largely based on experience and intuition. The data explosion and the rise of big data technology have revolutionized the field of business analytics and have provided unprecedented opportunities for data-driven transformation of the HR department. As talent competition between enterprises intensified,the use of big data to remodel human analysis and human resources management is essential for HR department to meet the challenges and keep long-term competitive advantage. We attempt to establish a theoretical framework of big data in human resources management at three levels（ HR analysis,HR department and organization） and systematically elaborate the changes and challenges brought by big data technology to human resource management. We also try to explain the inherent logic of big data. In HR function using multidisciplinary perspectives. Finally,the future research direction of big data in human resources field is discussed.
作者
姚凯
桂弘诣
Yao Kai;Gui Hongyi(School of Management, Fudan University, Shanghai 200433, Chin)
出处
《复旦学报（社会科学版）》
CSSCI
北大核心
2018年第3期146-155,共10页
Fudan Journal（Social Sciences）
基金
国家社会科学基金重大项目"大数据时代国际人才集聚及中国战略对策研究"(项目批准号:16ZDA057)资助
关键词
大数据
人力分析
人力资源管理
Big Data
HR Analysis
human resource management
