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Management Practices in Europe, the US and Emerging Markets. Nick Bloom (Stanford Economics and GSB) John Van Reenen (LSE and Stanford GSB) Lecture 7: Management experiments. Experiments in India Experiments in China. Does management matter: evidence from India.

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management practices in europe the us and emerging markets

Management Practices in Europe, the US and Emerging Markets

Nick Bloom (Stanford Economics and GSB)

John Van Reenen (LSE and Stanford GSB)

Lecture 7: Management experiments

slide2

Experiments in India

Experiments in China

does management matter evidence from india

Does management matter:evidence from India

Nick Bloom (Stanford)Benn Eifert (Berkeley)Aprajit Mahajan (Stanford)David McKenzie (World Bank)John Roberts (Stanford)

slide4

Management appears to be better in rich countries

Average country management score, manufacturing firms 100 to 5000 employees

(monitoring, targets and incentives management scored on a 1 to 5 scale. See Bloom and Van Reenen (2007, QJE) and Bloom, Sadun and Van Reenen (2010, JEP)) & ICP (2010)

4

slide5

Developing countries have more badly managed firms

US, manufacturing, mean=3.33 (N=695)

Density

India, manufacturing, mean=2.69 (N=620)

Density

Firm level management score, manufacturing firms 100 to 5000 employees

5

but do we care does management matter
Long debate between business practitioners versus academics

Evidence to date primarily case-studies and surveys

Syverson’s(2010) productivity survey stated on management

“Perhaps no potential driver of productivity differences has seen a higher ratio of speculation to actual empirical study than management”

But do we care - does management matter?
we investigate these questions in large indian firms
We investigate these questions in large Indian firms
  • Took large firms (≈ 300 employees) outside Mumbai making cotton fabric. Randomized treatment plants get 5 months management consulting, controls plants get 1 month consulting.
  • Collect weekly data on all plants from 2008 to 2010
  • Profits up by about 25% ($250,000 a year)
  • Productivity up by about 10%
the production technology has not changed much over time
The production technology has not changed much over time

Krill

Warp beam

The warping looms at Lowell Mills in 1854, Massachusetts

slide13

Exhibit 3: Many parts of these Indian plants were dirty and unsafe

Garbage outside the plant

Garbage inside a plant

Flammable garbage in a plant

Chemicals without any covering

slide15

Exhibit 5: There was almost no routine maintenance – instead machines were only repaired when they broke down

slide16

Exhibit 6a: Inventory was not well controlled – firms had months of excess yarn, typically stored in an ad hoc way all over the factory

slide17

Exhibit 6b: Inventory was not well controlled – firms had months of excess yarn, typically stored in an ad hoc way all over the factory

slide18

Exhibit 7: The path for materials flow was often heavily obstructed

Unfinished rough path along which several 0.6 ton warp beams were taken on wheeled trolleys every day to the elevator, which led down to the looms.This steep slope, rough surface and sharp angle meant workers often lost control of the trolleys. They crashed into the iron beam or wall, breaking the trolleys. So now each beam is carried by 6 men.

A broken trolley (the wheel snapped off)

At another plant both warp beam elevators had broken down due to poor maintenance. As a result teams of 7 men carried several warps beams down the stairs every day. At 0.6 tons each this was slow and dangerous

these firms appear typical of large manufacturers in brazil china and india
These firms appear typical of large manufacturers in Brazil, China and India

Experimental Firms, mean=2.60

Indian Textiles, mean=2.60

Indian Manufacturing, mean=2.69

Brazil and China Manufacturing, mean=2.67

19

Management scores (using Bloom and Van Reenen (2007) methodology)

slide20
Management practices before and after treatment

Performance of the plants before and after treatment

Why were these practices not introduced before?

20

slide23

Adoption of these 38 management practices did rise, and particularly in the treatment plants

.6

.5

.4

.3

.2

-10

-8

-6

-4

-2

0

2

4

6

8

10

12

Months after the diagnostic phase

Treated

Treatment plants

Control plants

Share of key textile management practices adopted

Control

Excluded plants(not treatment or control)

slide24
Management practices before and after treatment

Performance of the plants before and after treatment

Quality

Inventory

Output

Why were these practices not introduced before?

slide25

Poor quality meant 19% of manpower went on repairs

Large room full of repair workers (the day shift)

Workers spread cloth over lighted plates to spot defects

Defects are repaired by hand or cut out from cloth

Defects lead to about 5% of cloth being scrapped

previously mending was recorded only to cross check against customers claims for rebates
Previously mending was recorded only to cross-check against customers’ claims for rebates

Defects log with defects not recorded in an standardized format. These defects were recorded solely as a record in case of customer complaints. The data was not aggregated or analyzed

now mending is recorded daily in a standard format so it can analyzed by loom shift design weaver
Now mending is recorded daily in a standard format, so it can analyzed by loom, shift, design & weaver

27

slide28

The quality data is now collated and analyzed as part of the new daily production meetings

Plant managers now meet regularly with heads of quality, inventory, weaving, maintenance, warping etc. to analyze data

slide29

Figure 3: Quality defects index for the treatment and control plants

Start of Diagnostic

Start of Implementation

End of Implementation

97.5th percentile

Control plants

Average (♦ symbol)

Quality defects index (higher score=lower quality)

2.5th percentile

97.5th percentile

Average (+ symbol)

Treatment plants

2.5th percentile

Weeks after the start of the diagnostic

slide30
Management practices before and after treatment

Performance of the plants before and after treatment

Quality

Inventory

Output

Why were these practices not introduced before?

30

sales are also informed about excess yarn stock so they can incorporate this in new designs
Sales are also informed about excess yarn stock so they can incorporate this in new designs.

Shade cards now produced for all surplus yarn. These are sent to the design team in Mumbai to use in future products

slide33

Figure 4: Yarn inventory for the treatment and control plants

Start of Diagnostic

Start of Implementation

End of Implementation

97.5th percentile

Average (♦ symbol)

Control plants

97.5th percentile

Yarn inventory (normalized to 100 prior to diagnostic)

2.5th percentile

Average (+ symbol)

Treatment plants

2.5th percentile

Weeks after the start of the intervention

slide34
Management practices before and after treatment

Performance of the plants before and after treatment

Quality

Inventory

Output

Why were these practices not introduced before?

34

slide35

Many treated firms have also introduced basic initiatives (called “5S”) to organize the plant floor

Worker involved in 5S initiative on the shop floor, marking out the area around the model machine

Snag tagging to identify the abnormalities on & around the machines, such as redundant materials, broken equipment, or accident areas. The operator and the maintenance team is responsible for removing these abnormalities.

slide36

Spare parts were also organized, reducing downtime (parts can be found quickly) and waste

Nuts & bolts sorted as per specifications

Parts like gears, bushes, sorted as per specifications

Tool

storage organized

slide37

Production data is now collected in a standardized format, for discussion in the daily meetings

After (standardized, so easy to enter daily into a computer)

Before(not standardized, on loose pieces of paper)

daily performance boards have also been put up with incentive pay for employees based on this
Daily performance boards have also been put up, with incentive pay for employees based on this
slide39

Figure 5: Output for the treatment and control plants

Start of Diagnostic

Start of Implementation

End of Implementation

97.5th percentile

Treatment plants

Average (+ symbol)

Output (normalized to 100 prior to diagnostic)

2.5th percentile

97.5th percentile

Average (♦ symbol)

Control plants

2.5th percentile

Weeks after the start of the intervention

slide40
Management practices before and after treatment

Performance of the plants before and after treatment

Why were these practices not introduced before?

40

why does competition not fix badly managed firms
Why does competition not fix badly managed firms?

Bankruptcy is not (currently) a threat: at weaver wage rates of $5 a day these firms are profitable

Reallocation appears limited: Owners take all decisions as they worry about managers stealing. But owners time is constrained – they already work 72.4 hours average a week – limiting growth.

Entry is limited: Capital intensive ($13m assets average per firm), and no guarantee new entrants are any better

so why did these firms not improve themselves
Collected panel data on reasons for non implementation, and main (initial) reason was a lack of information

Firms either never heard of these practices (no information)

Or, did not believe they were relevant (wrong information)

Later constraints after informational barriers overcome primarily around limited CEO time and CEO ability

So why did these firms not improve themselves?

42

slide43

Finally, not to pick on the Indians, one country has such bad managers it even makes TV shows about them.......

David Brent(The Office)

Basil Fawlty (Fawlty Towers)

Jim Hacker

(Yes Minister)

slide44

Experiments in India

Experiments in China

working from home or shirking from home a chinese field experiment

Working from home or shirking from home?A Chinese field experiment

Nick Bloom (Stanford)James Liang (Ctrip)John Roberts (Stanford)

slide46

Policymakers are increasingly thinking about regulating issues around work-life balance

The EU regulates working hours to average 48 hours per week, with some countries (France) restricting this to 35 hours

Many European countries are also increasing maternity and paternity – i.e. Sweden offers 16 months paid joint leave

In the US working hours are currently not regulated, and statutory maternity and paternity leave is limited to 12 weeks unpaid.

slide48

The report highlights that changes in families and the labor market are increasing work-life pressures

so is this bad should the us regulate on work life balance
So is this bad – should the US regulate on work life balance?
  • Amazingly, it appears nobody really knows
  • Having been consulted on the CEA report it was clear the evidence base on this is extremely poor

Source: Executive summary, CEA report (2010)

so we are running field experiments on two potential solutions home working and part time working
Working with CTrip, China’s largest travel-agent with 10,000 employees, whose co-founder and chairmen is James LiangSo we are running field experiments on two potential solutions - home working and part-time working

52

slide58

So preliminary evidence suggests benefits for home-working

Happier employees

Lower quit rates

Reduced office costs (only in 1 day per week)

Question is will this persist in the long-run, and how much can this be extended to other firms and countries?

The JetBlue question

But home workers report much higher job satisfaction levels and 50% fewer quits