Data-Driven Decision Support Framework for Human Resource Strategic Planning

Human resources have become integral to every successful business, so companies without motivated and enthusiastic employees quickly become redundant. There has been an enormous change in the role of human resources as an operational, strategic component in recent years. This study aims to help a national organization refine its human resource (HR) strategy using the Data-driven decision support framework (DDSF) to navigate through existing reports, perform surveys and conduct in-depth interviews with organization management and experts to compile the information collection. Using SWOT analysis, human resource plans have been developed. Regarding internal and external variables, the organization under investigation is in an above-average condition regarding human resources. It is advised that the organization prioritize defensive strategies when preserving and producing human resources and aggressive strategies when entering human resources because it fails to perform well in external factors and is performing below average in these areas. In order to promote and enhance data-driven decision-making in HRM, policymakers will need to establish legal frameworks, data governance frameworks, innovation incentives and training and development programs. Firms using data to enhance labor management processes and promote organizational performance in digitalized environments might benefit from this framework’s incisive analysis and helpful advice. The results of the experiments prove that the proposed DDSF model may improve the efficiency and effectiveness of the organization.