Predictive HR analytics and talent management:a conceptual framework

Digitisation,new technologies and artificial intelligence demand organisations for new ways of working with a different skill set to accomplish strategic objectives.HR analytics is the scientific solution enabling organisations to make significant human capital and strategic business decisions and thereby gain a competitive advantage.However,theory-based relationships in HR analytics adoption is meagre.Further,there is a paucity of HR analytics literature on the role of contextual factors that affect organisations in building predictive HR analytics(PHRA)capability.Addressing this gap,we develop a conceptual framework through the lens of the Technological-Organisational-Environmental(TOE)framework and Resource-based theory to examine the relationships among the antecedents and consequences of PHRA capability considering talent management under the moderating effect of a data-driven culture.This paper is possibly the first study to propose a theoretical model to examine the effect of PHRA capability on talent management outcomes.

数据驱动型人力资源管理:述评与展望

数据驱动型人力资源管理(HR Analytics)是21世纪以来人力资源学术研究和实践创新的热门领域。国内外研究已对其的缘起、定义、特征、效用、实施路径、理论依据等有了一定认识。从内涵和特征看,HRA概念比"人力资源指标""人力资源计量"更加宽泛,其本质是以信息技术为基础、以可视化图表为手段,通过"数据+分析"实现对组织的诊断和预测,驱动和优化人力资源决策。作为实现战略人力资源管理的一种工具和技术手段,HRA是技术质变与实践应用的结合,目的并不在于构建理论,而在于解决生产中的实际问题、提升组织的业务效益。HRA的效用是为测量评估、分析汇报等提供可量化的证据,将人力资源流程、人员决策与业务成果、组织绩效等有效关联。其实施路径为:明确需要利用HRA解决的问题;通过先进的纵向多变量建模方法,回答问题;运用分析结果优化人力资源实践。未来HRA将与人工智能、机器学习等现代技术结合,广泛应用于人力资源招聘、培训、绩效管理等流程之中。