Background of the Study
Talent management has emerged as a key driver of business growth, especially in the manufacturing sector, where human capital is pivotal to operational success. Effective talent management involves attracting, developing, retaining, and optimizing employees' potential, thus aligning their skills with organizational goals (Koch & Stern, 2023). In Nasarawa State, the manufacturing industry faces numerous challenges, such as a shortage of skilled labor, high turnover rates, and ineffective training programs.
To remain competitive and achieve sustained growth, manufacturing firms in the state are increasingly focusing on talent management strategies, such as recruitment drives, employee development programs, performance management systems, and retention plans. However, despite these efforts, many organizations struggle to effectively integrate talent management into their business strategies. This study aims to critically analyze how talent management strategies impact business growth in manufacturing firms in Nasarawa State, focusing on the alignment between talent development and business objectives.
Statement of the Problem
The manufacturing sector in Nasarawa State continues to experience slow growth due to various challenges in managing talent, including the inability to attract skilled workers, a lack of robust employee development programs, and ineffective retention strategies. While many manufacturing firms have implemented talent management practices, there is limited empirical evidence on their actual impact on business growth in the state. This gap in knowledge presents an opportunity to explore the extent to which talent management strategies contribute to the success and growth of manufacturing firms (Aminu & Duru, 2023).
Objectives of the Study
Research Questions
Research Hypotheses
Scope and Limitations of the Study
This study will focus on manufacturing firms in Nasarawa State that have been operational for at least three years and have implemented talent management strategies. Limitations include potential biases in self-reported data and a limited number of firms willing to participate in the study.
Definitions of Terms
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