The concept of digital offboarding has taken a critical role in the organizations in the wake of the increasing cybersecurity threats and breach of information concerning the departing employees. Offloading of employees is a complex interplay between human resource management, information technology systems and data governance systems. The reason is that bad offboarding practices predispose the possibility of unauthorized access to data, intellectual property theft, and non-adherence to regulations to a high degree. The paper develops a critical path analysis model that assists to identify weak areas to digital offboarding operations and suggests a best practice framework that emphasizes the HR/IT integration to minimize the risk of data exfiltration. The study takes a mixed-methodology to integrate process mapping, risk modeling, and simulated enterprise workflow analysis. The study also indicates significant lags and gaps between the HR and IT operations that present loopholes that can be used by cybercriminals to infiltrate data. A formal architecture is proposed that includes automated access revocation, live communication, audit trails and predictive risk scoring system. The results indicate that at least 72% of data exposure windows are minimized during synchronized offboarding processes as opposed to the usual sequential models. Research contributes to the existing literature in the field of cybersecurity governance, as it proposes a risk mitigation model in the form of a process and offers viable recommendations to businesses that would like to enhance safe means of leaving their workers. The framework proposed is compliant with the requirements of different standards, including GDPR, ISO/IEC 27001, and NIST, which guarantees the efficiency in its functioning and adherence to the regulation.