BBW shows the way of improving; effectiveness of Bangladeshi RMG workers is better than that of INDIA
A recent report from Impactt, that enables organizations to improve working conditions and livelihoods across global supply chains in a way that brings clear business benefits to both ends of the chain, showed that some easily obtainable changes can improve factories profitability and that results better return to the workers. The project also revealed that the effectiveness of Bangladeshi RMG workers is better than that of India. The pilot project indicates that Bangladeshi workers are quick learners and adopt comparatively quickly to the developments. The project conductor Impactt is a consultancy firm specializing in ethical trade, human rights, labor standards and international development. Starting from 2011, published recently in 2013, with the launch of the UK Department for International Development’s RAGS (Responsible and Accountable Garments Sector) Challenge Fund, they saw the opportunity to build a coalition of retailers, brands and factories to develop a replicable and cost effective methodology to strengthen export garment factories in India and Bangladesh and supported to become better businesses offering better jobs for workers. ‘Nicer Work?’ is a comprehensive project of Impactt, presents the Benefits for Business and Workers Programme (BBW) 2011-2013, that aimed to develop a virtuous circle of competitive businesses with skilled, well paid, safe and loyal workforces producing excellent product. The program focused on export garment manufacturers in India and Bangladesh and was supported by a coalition of retailers and brands, initially Arcadia Group, Marks & Spencer, Mother care, New Look, Sainsbury’s and Tesco, subsequently joined by Ralph Lauren and Varner Group. All 73 participating factories made financial contributions and the program was benefited from matched funding from the Department of International Development’s RAGS Challenge Fund.
Curriculum of BBW:
Building a vision for each factory | |||
Setting clear targets for employee retention, absenteeism, efficiency, quality and workplace communications | |||
HR | Production- Improving Efficiency | Quality | Fire Safety |
Improve retention • Better induction • Introduce buddy system • Proper skills assessment and career progression | Improve production line flow • Line balancing • Capacity studies • Measure and analyse efficiency data • Capture and reduce non-productive time | Measurement • Understanding and reducing rework • Measuring and reducing Cut-to-ship losses | Review • Why is this important to our business? • Understand current systems • Difficulties within current systems |
Improve attendance • Convert unplanned into planned leave • Easy to use leave process • Increase attendance bonus | Improved methods • Method study and standardising operations • Better cross-departmental working | Incentives • Zero defect operators • Building ownership for quality | What good looks like • What needs to change? • Putting people first • How do we make better decisions in policy and implementation? • How can we keep this going on a daily basis? |
Formal structures & commitment to invest in people • Co-created job descriptions • Skills assessment and pro-active training programmes • Specific training for supervisors | Upskilling supervisors to proactively improve line performanceRewarding better performance • Production bonuses and incentives schemes | Tools • Tools and techniques to strengthen existing systems • Taking ownership • Technical requirements | |
Improved communication – Buddies, supervisor soft skills, committees | |||
Improved teamwork and cross departmental working and respect | |||
Problem solving skills and a ‘can-do’ attitude | |||
Professionalisation of management systems and managers |
Project outline:
Total program performed in two phases.
The Phase 1 focused on Building management skills and improving working conditions in 10 pilot factories in India and Bangladesh. From Phase it was learnt that ‘The model works’ method would give good result. They also understood that necessary training must be in local language, there should have more space for practical learning, co-creation and peer learning.
The Phase 2 stage Rolled-out for Scale-up – group training and implementation support for 63 factories.
Impactt and RBC worked closely with retailers and, in Bangladesh, the Bangladesh Garment Manufacturers Exporters Association (BGMEA) and UK Trade and Investment (UKTI) to recruit 63 factories for Phase 2. In India, the British High Commission hosted the launch event.
Measuring success
A set of indicators developed to measure the effectiveness of the program.
A. Good businesses indicators
- Efficiency – measuring how much product the factory actually produces against its theoretical capacity.
- Cut-to-ship ratio – a measure of quality, which looks at how much of the fabric cut is made into finished garments which pass the final quality inspection. In knitting factories, we measure the yarn-to-ship ratio. Spoiled and wasted garments are a major financial loss to many factories.
- Worker absenteeism – measuring how motivated workers are to come to work on time each day.
B. Good jobs indicators
- Average take-home pay – workers’ total income including overtime payments and bonuses. This is what matters to workers and enables them to pay the bills.
- Average hourly pay – this enables us to look at whether workers are getting more or less money per hour that they work.
- Worker turnover – a proxy for job satisfaction, reducing worker turnover indicates that workers are more satisfied with their jobs and choose to stay.
Success factors:
Looking in more detail at the results, and the profiles of the factories, it has been seen a pattern in terms of which factories tend to do better, and which less well in Bangladesh.
- Factories with more sophisticated production systems tend to have a better performance in improving efficiency. These factories also appear to perform better at reducing absenteeism. However, there does not appear to be a link between the level of production sophistication and increases in pay or worker turnover. This indicates that this methodology supports increases in pay and job quality, regardless of the sophistication of production systems.
- Factories which attended all the training sessions, updated their action plans and proactively contacted trainers for support if they faced problems were more successful than less engaged factories, particularly in terms of increases in pay per hour, cut-to-ship and efficiency.
- Factories were more likely to be engaged in the program if they have a stable, long term relationship with their buyer.
- Piece rate factories (producing sweaters) outperformed those paying monthly salaries significantly in pay-related indicators. For example pay per hour in the pilot line increased by 35% in piece-rate factories compared to 10% in monthly rate factories. Improvements in production efficiency directly impact piece rate workers’ ability to produce more pieces in an hour. This means workers experience a faster rate of increase in their wages.
- Larger factories appear to perform better across all productivity indicators, for example cut-to-ship increased by 2.33% at large factories compared to 0.73% at small factories. This is probably because they are more likely to have more sophisticated production systems and more staff available for training. Large factories’ higher volumes mean that the financial impact of cut-to-ship improvements is significant. The production teams are therefore incentivised to continue to pour resources into productivity improvements.
- There is no meaningful difference between the results of factories that were required to join the program by their buyer and factories that were asked to join the program (optional). In fact 75% of compulsory factories were highly engaged (6 out of 8) compared to 42% (11 out of 26) of optional factories.
BANGLADESH RESULTS | INDIA RESULTS | ||||||
Parameters | Start | End | % Change | Parameters | Start | End | % Change |
Efficiency | 47.00% | 55.59% | 18.28% | Efficiency | 40.92% | 51.66% | 26.25% |
Cut-to-ship ratio | 95.55% | 96.64% | 1.14% | Cut-to-ship ratio | 95.86% | 97.18% | 1.38% |
% of workers taking unplanned leave (per month) | 7.90% | 5.24% | -33.67% | % of workers taking unplanned leave (per month) | 14.44% | 10.58% | -26.73% |
% labour turnover (per month) | 9.72% | 4.65% | -52.16% | % labour turnover (per month) | 11.62% | 8.59% | -26.08% |
Average take-home pay (Taka) | 6,430 | 6,921 | 7.64% | Average take-home pay (Rupees) | 5,197 | 5,461 | 5.09% |
Average hourly pay(Taka) | 25.87 | 28.96 | 11.94% | Average hourly pay(Rupees) | 23.36 | 25.22 | 7.96% |
Average working hours (basic + OT hours) | 250.10 | 243.63 | -2.59% | Average working hours (basic + OT hours) | 216.83 | 212.03 | -2.21% |
% workers working more than 60 hours per week | 42.11% | 23.80% | -43.48% | ||||
Table 2: Comparison on improvement results between Bangladesh and Indian Garments Workers. |
Comparison between BBW and Non-BBW factories:
BBW factories compared to a group of 28 comparable factories which did not participate in the BBW program. Factories in both groups were broadly similar, in terms of location, product type, price point, export volume and type of customer. Impactt visited these factories to carry out audits or consultancy work during the period over which the BBW program was carried. It is found that BBW factories performed far better overall on all key labour issues in which the project monitor, in India and in Bangladesh.
In Bangladesh in BBW factories the project found no incidence of forced labour, non-payment of minimum wage, child labor and harassment and reduced incidence of coached workers, double books and hours over 60 per week, whereas in non-BBW factories, we found forced labour, in the form of illegal deductions from salaries, in 50% of sites, non-payment of minimum wage in 11%, child labour in 13%, harassment in 57%, coached workers in 18% and double books in 43%.
In India, BBW participants also had lower incidence of labour standards issues than non-participants. In BBW factories, there were no instances of forced labour, non-payment of minimum wage, child labour, harassment and coached workers, and lower incidence of hours over 60 per week, no/ineffective worker representation and double books. Whereas in non-BBW factories, Impactt found workers working over 60 hours per week in 100% of the factories we visited, non-payment of minimum wages in 25%, child labour in 13%, lack of robust age verification in 60%, no or ineffective worker representation in 100%, harassment in 11% and coached workers and double books in 27%.
Findings:
Table 1 shows a comparison on development made between Bangladeshi and Indian garments workers after a well developed 6 month training to key managers in problem-solving and decision-making techniques, and upping their skills in HR management, communications, production and quality management.
The comparison indicates that Bangladesh is performing better than India in many parameters. It is to be mentioned that the project was not objected to compare the industries of two countries; rather the report reveals the same indirectly. It is also seen that the BBW method shows greater impact in Bangladesh than India.
Factories contributed the equivalent of £2,000 to participate. Over its two years, BBW reached a total of 102,110 workers, 54,186 (53%) of them women. In Bangladesh the project reached 41 factories employing 80,526 workers (57% women) and in India, they reached 32 factories employing 21,584 workers (38% women). Presence of woman is higher in Bangladeshi apparel industry is really appreciable.
Looking at wages, in both Bangladesh and India, BBW factories at the end of the program were paying significantly more than non-BBW factories, with fewer incidences of long working hours. In Bangladesh, 1730 Tk or 25% more per month, and in India 158 Rs or 3% more per month. However, in neither country did wages approach current estimates of living wage. Nevertheless, the project has clearly been successful in putting more money into workers’ pockets, both in comparison to the amount they received earlier, and in comparison to other equivalent factories.
Table 2 represents a significant saving for factories. On average, participating factories of Bangladesh saved £40,293 during the 6 month course, due to cut-to-ship improvements, a return on their initial investment (£2,000) of more than 21 over 6 months. The program championed investment in the workforce, proper induction systems, better communications and better access to skills development and promotion, increasing employee satisfaction and prompting a sense of self-worth. Overall, the program has supported factories to make progress on pay, with an increase in average take-home pay of 491 Taka per month or 7.64%. This would be equivalent to an increase in annual pay of £3.4 million across the 67,640 workers employed by participating factories.
Conclusions:
The pilot project explained here, may not change the whole picture of the RMG industries here in Bangladesh rather such outcomes clearly shows that if the factories try to make effort they can really improve return from their existing resources. Improved management of resources is must in a world of a growing cost. When the industry owners are looking for solutions for paying higher wages, such systemic approach of improving productivity can help them a lot. Endless worker unrest can be mitigated by approaching ‘good business’ & ‘good job’ methodology.