Community Research and Development Information Service - CORDIS


RMGPP Report Summary

Project ID: 669746
Funded under: H2020-EU.1.1.

Periodic Reporting for period 2 - RMGPP (Productivity and Development: The Ready-made Garment Productivity Project)

Reporting period: 2016-08-01 to 2018-01-31

Summary of the context and overall objectives of the project

Differences in productivity explain much of the differences in income levels across countries, yet little is known about how to improve productivity of manufacturing in the developing world. Recent research reveals very high dispersion in productivity in low-income countries. We examine firm productivity at a uniquely detailed level, collecting data from hundreds of garment manufacturers in several countries. The data, coupled with a new method for comparing productivity, allow us to measure physical productivity in and across firms and among heterogeneous products. Initial results from nearly 100 factories in Bangladesh show significant dispersion of productivity within factories; production lines at the 90th percentile are 50% more efficient than those at the 10th percentile. Differences are highly persistent – puzzling given that the lines are often on the same production floor. Capital and the quality of the buyer explains a small part of the dispersion: lines producing goods for higher-end buyers are significantly more efficient.

Shocks and interventions allows us to examine the challenges of increasing productivity in volatile conditions characteristic of low-income countries. Our data span a period including general strikes and a 67% minimum wage increase. We have conducted 2 RCTs on line supervisor training. We are designing data collection and analysis tools for use by factories and a program to address issues related to worker stress.

The overall objective is to improve our understanding of how productivity evolves over time, how it varies across and within firms, and why lower-productive firms survive even in competitive markets. These questions are fundamental for understanding growth dynamics in developing economies.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Production Efficiency in the Readymade Garment Sector: To date we have carried out analysis on a project evaluating the effectiveness of a consulting intervention implemented by Impactt Consulting, Ltd. WThe consulting intervention was fully delivered in 25 large factories, and the analysis as based on both administrative records and baseline plus two follow-up surveys conducted with production workers and managers in participating factories. The initial results suggest that the consulting intervention did lead to some significant changes in practices and outcomes, but that these changes were quite modest in magnitude. We are still working to understand why even the most straightforward of the practices taught in the program had such low take-up rates among participating factories.

Work Progression Toolkit: A second project central to the work carried out to date was undertaken in collaboration with the International Finance Corporation (IFC, a unit of the World Bank) and the IFC / ILO Better Work Bangladesh program. The goal was to develop and test a module for the Better Work program that prepared female sewing machine operators to move into management positions. (Around 75 per cent of production floor workers in the sector are female, while 95 per cent of supervisors are male.) Fieldwork for this project was carried out in 27 factories during this reporting period. The factories nominated 240 female sewing machine operators for training. We completed diagnostics for each of the nominees, who then attended training and received trials as assistant line supervisors. Trainees were randomised to receive soft skills training alone, or soft skills training combined with technical training at the start of the trial period. Initial analysis of the data indicates that the combined soft-skills and technical training was effective in the transition to supervisory roles, while the soft skill training alone was not. Importantly, we find that diagnostic scores reflecting attitudes of the trainees at baseline predict both completion of the training program and effectiveness as a line supervisor. In particular, the extent to which the trainee’s family supports her working as a supervisor predicts completion of the training program, and the trainee’s initial confidence in her ability and desire to work as a supervisor predict performance in the role. We are presently discussing the results with the IFC and Better Work with the aim of helping them scale the project in Bangladesh and perhaps other countries.

“Small-n” project: We are developing a new project working intensively with a small number of factories in Bangladesh. The data we have collected from the larger sample of factories reveals two patterns: 1) There are substantial productivity differences across factories; and 2) There is substantial and persistent variation in productivity across production lines within factories. These patterns raise questions of differences in management practices across factories, and across lines within factories. For example, what prevents factories from spreading lessons from highly productive lines to less productive lines? The “small-n” project is designed to provide insight to this question. We begin by analysing production data from the participating factories, including an analysis benchmarking their outcomes to averages across other factories in the industry. This analysis tis a first step in designing a set of interventions to be implemented at the line- or floor-level. We then measure and report to factory management the outcomes of these interventions. We are interested in understanding both issues that arise when the interventions are implemented, and the way management uses the information provided on the outcomes of the interventions. We believe both of these will contribute to the literature on productivity and management practices by deepening our understanding of the decision-making processes within firms, and how th

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The project is generating data from administrative records of factories that provide an unprecedented level of detail on productivity across factories, and across production units within factories. While we have encountered challenges in making the data fully comparable across factories, we are beginning to address those challenges. We remain confident that the data collected through the project will allow us to make a significant contribution to our understanding of productivity dynamics in the manufacturing sector in developing countries.
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