Beyond COVID-19: How the manufacturing industry should prepare

How To Screen For or Train A Good Manager?

FOCUS AREA

Improving Work Environment

LOCATION

Karnataka

REACH

41 factories, 70,000 workers

PARTNERS

University of Michigan

STAGE

DESIGN

EVALUATE

ANALYZE

DISSEMINATE

SCALE-UP

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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.

Challenge

Identifying and training workers to be good managers is costly and difficult, particularly for low-margin, labor-intensive manufacturing firms in developing countries.

Scoping / Proof Of Concept

We have rigorously evaluated the following by way of two large-scale randomized controlled trials in Indian garment factories over the last three years:

  1. We identified which managerial skills, practices, and traits best predict productivity in low-income contexts. We then documented that these characteristics are undervalued in the labor market partly because they are difficult and costly to measure.

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’]

  1. We developed a soft skills training program for supervisors and mid-level managers. The training addresses topics such as communication, self-esteem, gender sensitivity, problem solving, work planning, and preventing harassment at the workplace.

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.

Design

We aim to translate the above two interventions into respective mobile-based application platforms:

  1. Our screening application will help identify the best candidates to hire for or promote to managerial roles by scoring them on their managerial skills, practices, and traits. It will also identify deficiencies in current stocks of these skills for the candidate.
  2. Our cross-cutting application technology will deliver targeted training modules to fill in the deficiencies identified in (1).

The applications are being co-developed with the trainers and supervisors by utilizing a human centered design approach at Shahi Exports. 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 41 garment manufacturing factories. During the evaluation phase, the projects will impact ~70,000 frontline workers.

Scale up

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



Ann Arbor
701 Tappan Ave,
Ann Arbor, Michigan 48109, United States
Bengaluru Corporate Office
Bellandur Gate, Sarjapur Main Road
Bengaluru, Karnataka 560102,
India
Delhi NCR Corporate Office
F-88, Okhla Industrial Area Phase-1
New Delhi, Delhi 110023,
India
Medellin
University EAFIT
Medellin, Colombia