A roadmap for managing an ageing workforce in the manufacturing sector: An Italian case study

Managing an aging workforce presents increasing challenges across industries, particularly in physically demanding sectors such as manufacturing. Key issues include knowledge transfer, worker retention, and maintaining productivity in operational environments that strain older workers. Northern Italy, a region with a strong manufacturing base, provides a relevant context for examining these challenges. This study applies the "Models and Methods for an Active Ageing Workforce" (MAIA) framework, which addresses six domains critical to supporting older workers: organizational culture, work design, health management, knowledge transfer, intergenerational coexistence and retirement pathway.

A case-based methodology was employed within a multinational manufacturing company in Northern Italy. Data were collected through qualitative and quantitative approaches, including stakeholder interviews, workplace observations, and targeted surveys assessing physical and mental workload. Analysis of this data, combined with discussions involving managers, foremen, and HR representatives, informed the development of a comprehensive roadmap for managing the aging workforce. The roadmap identifies key addressed areas and critical gaps and proposes targeted tools and actions to improve work conditions for older employees. This approach demonstrates the practical application of the MAIA framework and the ISO 25550:2022 standard in an industrial aging workforce context.

The study highlights the importance of a structured framework for managing aging workers in physically demanding environments. By identifying specific challenges and proposing actionable solutions, the developed roadmap supports effective workforce planning and management. The results contribute valuable insights into optimizing organizational culture, health management, knowledge transfer, and retirement planning to promote sustainable employment for older workers in manufacturing.