Abstract

As organizations face unprecedented uncertainty as they navigate a complicated and fast-changing world, the ability to anticipate and adapt to workforce shifts has become more crucial than ever. This thesis examines how future foresight and strategic planning in human resource management (HRM) can reinforce organizational adaptability and maintain a competitive edge. By analyzing key drivers of change—including technological advancements, demographic shifts, political dynamics, and socio-economic trends—the study identifies innovative HRM strategies that enable organizations to address emerging workforce challenges and opportunities proactively. Through a structured evaluation of foresight techniques, this research highlights best practices for cultivating a resilient and future-ready workforce. The research utilizes a multi-method approach, including PEST analysis, expert interviews, and an assessment of future foresight methods, to examine the external forces shaping HRM. The findings indicate that traditional HR strategies are increasingly insufficient in today's fast-paced environment, especially for managing the complexities of modern workforce changes. Instead, structured foresight techniques—such as trend analysis and scenario planning—prove instrumental in helping HR professionals navigate uncertainties, optimize workforce planning, and enhance talent retention. The study contributes to HRM by bridging the gap between traditional personnel management and strategic foresight. It underscores the significance of integrating strategic foresight practices to anticipate political, economic, social, and technological shifts affecting workforce management.

Library of Congress Subject Headings

Employment forecasting; Personnel management; Strategic planning--Data processing

Publication Date

2025

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Ozcan Saritas

Campus

RIT Dubai

Plan Codes

PROFST-MS

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