Challenges of change: Training women to manage in the Bangladeshi - - PowerPoint PPT Presentation

Challenges of change: Training women to manage in the Bangladeshi garment sector

Atonu Rabbani, Department of Economics, University of Dhaka

Joint work with Rocco Macchiavello, Andreas Menzel and Christopher Woodruff UNU-WIDER Conference on Human Capital and Growth Helsinki, June 6, 2016

Managing people ably is important

Management is important

Data suggests a long tail of “bad” firms at the left tail

• f the distribution in

the developing countries.

• ne quarter of

cross-country productivity differences can be explained by differences in management practices.

• Bloom , Sadun

and Van Reenen (2015)

y = -0.1753x + 2.287 R² = 0.7647

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 7 8 9 10 11 12 Proportion of Firms below Global Median Log (GDP per employed Labor)

Moreover…

There is a huge potential to gain in terms of productivity within firms as well.

Note: Based on 42,000 line-days worth of data from 7 factories. Source: Machiavello, Rabbani and Woodruff (2015)

75th percentile line is more than 1.5 times more productive compared to the 25th percentile line!

Context and Questions

Addressing some of these issues at RMG Sector in Bangladesh

• Very large: about 4m people involved in the sector
• Moreover, 65% is female
• At the sewing lines: 70-80%
• However, less than 5% of the supervisors are women
• Why?
• Marginal female supervisor is worse than male supervisor
• OR, NOT, suggesting managerial talent is misallocated
• Worse or not, women are perceived as being worse in supervisory

roles

• Not trying them as supervisors can contribute to persistence in

such perceptions

Design

Design and Data Collection

• Just observational data will not be useful: too few women

supervisors and endogenous assignments

• So we work with 24 suppliers of a single large foreign

buyer

• Factories nominated operators for a GIZ-designed six-

week offsite training on production, quality and HR/compliance

• Factories selected 96 men and 121 women for training –

72 men and 73 women finally completed the training

Randomization

• Factories were randomly allocated into either rounds 1

and 3 or rounds 2 and 4

• Trainees from each factory were randomized either 1 or 3

and similarly either 2 or 4

• Then trainees were randomly assigned among the trial

lines

• We collected data…
• …before the trainings started (Findings 1 and 2): skill assessments,

perceptions

• …right after the six-eight week of trials and a further two-four month

follow-ups (Findings 3): production data

• …further follow-ups (Findings 4): “production management” games

Findings

Finding #1

• In broadly defined eight sets of tasks, women are

perceived as weaker supervisors

• Consistent across the whole managerial hierarchy,

including the operators

• Women are considered less able to understand

machines and operations

• These perceptions are slightly weaker among the

female operators and those who have worked under female supervisors

Perceived Ability by Gender in Supervisory Roles

Negative means men are perceived as better supervisors Most people think so. And across almost all tasks.

• 1.00
• 0.80
• 0.60
• 0.40
• 0.20

0.00 0.20 0.40 HR Managers Production Managers Line Chiefs Line Supervisors Line Operators

Perceived Ability cont.

Female trainees have more favorable views followed by female

• perators.

Average male

• perators have the

least favorable views. Exposure to female supervisors mitigate some of the bias.

• 1.00
• 0.80
• 0.60
• 0.40
• 0.20

0.00 0.20 Female Operators Male Operators LO's worked w/ female SV Female trainees Male trainees

Finding #2

• Before the training, using extensive skill

assessments, we find

• Female and male trainees have similar technical

knowledge of machines and operations contrary to widely-held beliefs

• However, women are chosen less in simulated

management games

• Women themselves rate themselves lower in the same

eight broad sets of tasks

Based on extensive skill assessments

1.19

• 0.09

0.22

• 0.27
• 0.6
• 0.47

Aptitude score Percentage drawings correct Drawing, "soft" score Communication, "soft" score Leadership, "soft" score Self confidence* Not much statistical differences Female trainees lack confidence (which disappears after the training)

Finding #3

• Using detailed line level productivity data, we look

at efficiency, quality defects and absenteeism

• Immediately after the training, initially the female

supervisor perform worse

• This gap disappears after few months at the line

Finding #3

Efficiency Defects

• 0.0093

0.0236 0.0176 0.0196 Female trainee Male trainee** Female trainee Male trainee Trial period Post-trial

• 0.002
• 0.0042
• 0.0055
• 0.0013

Female trainee Male trainee Female trainee* Male trainee Trial period Post-trial

Finding #4

• The experiment also allows us to understand change in

attitude towards female line supervisor

• Female trainees are ranked almost a point lower
• Male operators rank the female trainees lower than female
• perators (-1.39 as oppose to -0.65)
• Male operators also hold more pessimistic view toward prospect of

promotion to supervisory roles in future and report leaving the factory sooner

• In simulated management exercises, the female trainees
• utperform the male counterparts (by 0.29 SD higher payoffs), but

NOT when a male operator is in the group

• The promoted trainees do even better
• Female leaders are ranked lower and less able to identify the

“correct” strategies

Conclusions

Some parting remarks

• Women are expected to be worse in supervisory positions

in any number of tasks, while evidence suggests

• therwise
• Signaling may be difficult as women are not tried in

supervisory positions

• Factories may tend to internalize the perception and the

attitudes, rendering changing the equilibrium challenging

Thanks for listening