摘要
针对人力资源配置不均衡的问题,提出一种基于多源大数据融合的优化方法,综合考虑员工能力、岗位需求等因素,明确配置优化目标。通过挖掘多源数据以深入分析人力资源特征,构建胜任指数与人岗匹配度目标函数,并设置相应约束条件,实现人力资源的最优配置。实验结果表明,该方法能够有效提升人力资源配置的均衡性,降低管理成本,提高员工满意度与企业整体绩效,为企业实现高效人力资源管理提供了有力支持。
Aiming at the problem of uneven allocation of human resources,an optimization method based on multi-source big data fusion is proposed,which comprehensively considers multidimensional factors such as employee abilities and job requirements,and clarifies the optimization objectives of allocation.By mining multi-source data to deeply analyze human resource characteristics,constructing a competency index and job matching objective function,and setting corresponding constraints,the optimal allocation of human resources can be achieved.The experimental results show that this method can effectively improve the balance of human resource allocation,reduce management costs,enhance employee satisfaction and overall enterprise performance,and provide strong support for enterprises to achieve efficient human resource management.
作者
李刚
LI Gang(Joint Logistic Support Force,Wuhan 430014,China)
关键词
多源大数据融合
优化配置
人力资源
multi-source big data fusion
optimization allocation
human resource
作者简介
李刚(1986-),硕士,研究方向:大数据赋能人力资源。
