A Big Data-Enabled Model for Optimizing Corporate Governance Decisions and HR Allocation

Abstract

In the context of rapid digital transformation, modern enterprises generally face the problems of scattered data, disjointed decision-making, and executive layers, as well as lagging resource responses, in the process of governance decision-making and human resource (HR) allocation. In light of these practical difficulties, the authors constructed a collaborative optimization model of governance decision-making and HR allocation that is based on big data analysis against the background of real business operation scenarios. By integrating external governance indicators, enterprise HR data, and business operation logs, a cross-domain data closed loop is formed, and on this basis, the authors designed a decision support model to realize the dynamic collaboration between governance constraints and human scheduling. This research provides a feasible practice path and case reference for enterprises to optimize governance and HR allocation by using information technology in complex environments.