Bridging the Gap: Prescriptive Human Resources Analytics Training to Enhance Performance of Employees in Higher and Tertiary Education Institutions (HEIs) in Zimbabwe
Keywords:
Human Resources, Higher and Tertiary Education, Prescriptive Human Resource Analytics, Performance, ZimbabweAbstract
This study assessed the eff ectiveness of prescriptive human resource analytics (PHRA) in enhancing employee performance within five state universities in Zimbabwe. Prescriptive analytics employs complex algorithms that prioritise accuracy over interpretation, offering organisations actionable strategies for achieving desired outcomes. Guided by the LAMP model for evaluating the outcomes of HR actions, the study adopted a qualitative research approach and an explanatory research design to explore participants’ perceptions of the relationship between PHRA and employee performance. Using purposive sampling, data were collected through structured interview guides and analysed thematically. The findings revealed that HR departments need to build structured plans to organise workforce data and integrate it with multiple organisational data sources to enable eff ective use of prescriptive analytics. Results further indicated that PHRA is particularly beneficial in transactional contexts, such as evaluating the success of specific training programmes, or identifying skill needs in selected organisational units through attrition pattern analysis. These insights demonstrate PHRA’s potential for improving employee outcomes when eff ectively embedded into HR systems. The study recommends that Higher Education Institutions (HEIs) in Zimbabwe adopt HR technologies that facilitate prescriptive analytics, enabling them to identify employee needs, design targeted training, and ultimately enhance workforce performance.
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