Developing a New Construction Supervisory Training Programme Focusing on Productivity and Performance Improvement of Labour Operations

Good supervision practices bring out the best labour outputs in construction. The lack of competencies of construction supervisors yields significant impacts on the labour performance in the construction sector of many countries. This study intends to develop a new construction supervisory training programme and relevant practices for addressing the industry’s evolving challenges related to the performance and productivity of labour with a long-term focus. The study methodology encompassed the applications of relevant generalised training models and a series of meetings, discussions and workshops conducted among academic and industry experts. The problemfocused and action-oriented communication approaches were used throughout the training development practices with the consideration of emerging characteristics of the industry. The developed training programme contains outcome-based learning practices in construction supervision that address the industry’s challenges related to the performance and productivity of labour. The study has further presented the ways for the resource arrangements and the formation of ground rules to lay the platform for the training delivery with a long-term focus. The proposed training programme provides a common template that includes generalised processes for developing new training programmes and filling the gaps in existing training programmes based on the industry needs through proactive education and training strategies. The study outcomes provide a bridge that combines institutional and industry practices towards strengthening the industry’s long-term focus on reskilling and upskilling to the new normal situations. Though the scope of the study was limited to the Sri Lankan context, the findings can contribute to creating a significant impact on construction education and training development practices in other developing countries in similar scenarios.