The widening productivity gap between rich and poor countries is, in part, explained by differences in firms’ managerial practices. In most low-skill manufacturing contexts in the developing world, like garment and textile firms which employ ~65 and 75 million people worldwide, productivity, wages, and worker retention are all extremely low.
Identifying and training workers to be good managers is costly and difficult, particularly for low-margin, labor-intensive manufacturing firms in developing countries.
We have rigorously evaluated the following by way of two large-scale randomized controlled trials in Indian garment factories over the last three years:
With the aim of reducing the cost for firms, we developed a screening questionnaire and analysis algorithm, which ranks candidates on managerial dimensions hitherto unaccounted. [read more in ‘Managerial Quality and Productivity Dynamics’]
Preliminary analysis indicates that the training made production lines 8% more efficient, and that female workers with trained supervisors were 20% less likely to report workplace harassment.
We aim to translate the above two interventions into respective mobile-based application platforms:
The applications were developed with the trainers and supervisors by using a human centered design approach at Shahi Exports. We are currently piloting the applications in Shahi Exports' factories. Undergoing this process will allow us to later contextualize the application when we take it to other firms.
To test the efficacy of the developed application, we will evaluate this mode of delivery through a randomized controlled trial in 53 garment manufacturing factories. During the evaluation phase, the projects will impact ~70,000 frontline workers.
Few tools or services currently exist to measure these types of managerial qualities for labor-intensive industries in developing countries. Given the sheer scale of the workforce, high rate of worker turnover, and average educational background, existing technologies are too expensive to be utilized for an extended period and at scale. Moreover, they fall short in addressing issues contextual to this industry.
Our application will allow for self-administration and efficient scaling. This low-cost mode of delivery, backed by rigorous testing, will not only deliver returns for firms via productivity and worker retention, but also welfare gains for workers.
We foresee that these ideas can apply more broadly to other garment manufacturing firms concentrated in low to middle income countries such as those in Bangladesh, China, Ethiopia, and Vietnam.
Image credits: Nayantara Parikh