understanding productivity in pakistani garments (pilot project)
TRANSCRIPT
Understanding Productivity in Pakistani Garments (Pilot Project)
R. Creedon, J. Krstic, R. Mann, K. Ruffini, M. Skuodis, K. Smula, M. Vlekke
September 2014 IGC – Growth Week, Pakistan
Azam Chaudhry
Mahvish Faran
Rocco Macchiavello
Theresa Thompson
Chris Woodruff
Lahore School of
Economics Lahore School of
Economics Warwick University Lahore School of
Economics Warwick University
Main Motivation DEVELOPMENT PERSPECTIVE
• Garments and Textile industries historically associated with “structural transformation”
• A laboratory to understand broader issues underlying persistent productivity differences across similar production units
GLOBAL PERSPECTIVE
• China accounts for approx. 30% of world’s RMG exports. • Increase in wages in China enormous opportunity for other
countries: Bangladesh, Myanmar, Ethiopia, Pakistan … PAKISTAN PERSPECTIVE
• International Trade & Policy Environment • Job creation: Garments vs. Textile
Within Asia, Declining Competitiveness Of China Lending Opportunity To Other Low Cost Countries
Source: Werner International, Textile Intelligence
0.7 0.8 0.9
1.9 2.1
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2002 2004 2007 2008 2011
Labour Cost (USD/hr) in Textile Industry, China TurkeyChina, coastalIndiaIndonesiaVietnamPakistanBangladesh
Widening gap in labour cost of
China and other Asian countries
3 Main Motivation
What do we plan to achieve ?
1. INTERNATIONAL BENCHMARKING • Compare productivity and managerial practices across firms
and countries (building upon data collection in Bangladesh)
• Target IGC countries: Pakistan, Myanmar, Ethiopia, India
• Develop a benchmarking tool to be give to factories
2. PAKISTAN CONTEXT • Design interventions to increase productivity grounded on a
detailed understanding of constraints and best practices
Pakistan: What have we achieved? 1. COMPLETED DATA COLLECTION FROM 7 FACTORIES
• Focus on Lahore (an estimated population of XYZ factories) • Sample selected by building relationships with associations and
buyers, possibly representative of broader sector: • 4 Large firms, • 1 Medium sized firms, • 2 Small firms.
• (Line supervisors survey ongoing)
2. PLANNING AND FORMULATION OF INTERVENTIONS • Likely to focus on either information and/or quality • Strengthened relationships with stakeholders:
• FACTORIES • BUYERS & OTHER STAKEHOLDERS
Data collected for 3 months [Feb. 1st to Apr. 30th ] Data entry expected to be completed by December 2014
Production & HR Data: Overview Factory Size Production
System (lines/mixed)
Data Quality
Supervisor Survey (yes/no)
Main Products
OP SUP
AA 518 28 line High yes Polo Shirts, Hoods
BB 910 28 line High yes Denim Jeans, Jackets and shorts
CC 1800 18 line High yes Denim Jeans
DD 510 12 line High yes Denim Jeans
EE 105 3 line High yes Knit Tops, Knit Bottoms, Woven Tops, Woven Bottoms, Scarfs
FF 1400 20 line Low/medium Yes at least 10 Polo Shirts, Hoods
GG 100 2 mixed low Yes Denim Jeans
Supervisor Surveys • In 7 factories we conduct surveys with (line) Supervisors. The
population consists of 111 Supervisors. We estimate to survey 95 supervisors in total. Some of them will be production supervisors while some will be quality supervisors/Inspectors.
• Survey currently in the field (completion in September/October 2014)
• Focus: - line level practices, - worker’s well-being, - quality, - authority - compensation to workers
Spot the Difference PAKISTAN
Spot the Difference PAKISTAN
BANGLADESH
Measuring Productivity • Measuring physical productivity when units of outputs are
heterogeneous (apples and oranges) is challenging
• Need a way to convert physical output of heterogeneous products into a common unit
• Each piece of garment comes with a SMV (or SAM): standard minute value (or allowance): time required to produce 1 piece of garments*
Measuring Productivity
Measuring Productivity
Measuring Productivity • Measuring physical productivity when units of outputs are
heterogeneous (apples and oranges) is challenging
• Need a way to convert physical output of heterogeneous products into a common unit
• Each piece of garment comes with a SMV (or SAM): standard minute value (or allowance): time required to produce 1 piece of garments*
• This allows us to measure (heterogeneous) output using (homogenous) time units
Efficiency= = # output pieces * SMV
# operators * runtime
Output Minutes
Input Minutes
Watch Your Neighbours: Efficiency Around the Globe
Countries Average Pay-
out (USD p.m.)
Key Product Category
Country Average
Operational Efficiency
Labour Pool Technological Advancement
FTA / GSP with Major Markets
Raw Material Availability
China 220-270 All Products 55-57% 813.5 mn High - All
Indonesia 170 Woven Synthetic 44-46% 113.7 mn Medium EU, US, Japan Synthetic Fibre
Vietnam 120 All Products 40-42% 46.5 mn Medium EU, US, Japan, Aus. & NZ None
Pakistan 116 Denim 42-44% 53.8 mn Medium EU, China Cotton
Cambodia 88 Denim, Woven 42-44% 8.0 mn Medium EU, US, Japan, Aus. & NZ None
Bangladesh 83* Knitwear, Woven Bottoms 38-40% 70.9 mn Low EU, Japan, Aus.,
Canada, US1 None
India 130 All Products 44-46% 467.0 mn Medium Japan, EU2 Cotton
Source : Technopak Analysis
1- GSP with US has a negligible impact on T&A exports from Bangladesh to US, 2- EU- FTA under discussion,
Dispersion Across and Within Units 0
.02
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0 20 40 60 80Efficiency (Output Minutes / Input Minutes)
TFP Disp. (Across Factories) TFP Disp. (Within Factories)
Across factories 75th / 25th: 1.95 ; 90th/10th = 2.79 Benchmark (Syverson 2004): 75th / 25th = 1.92; 90th/10th = 4.02 Within factory (across lines) 75th / 25th = 1.22; 90th/10th = 1.64
Sample: preliminary data from 5 Bangladeshi factories
Benchmarking Tool
• Adequate firms capabilities • Benchmarking against other firms in same country/other country
Introduction
Select the time period for analysis
Select the month for analysis
Select the date for analysis.
Financial MetricsA. Labor Cost per Earned Minute (Tk) B. Average Cost for Wasted Time (Tk)
0.9 0.6 1.5
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Line-04 Line-05 Line-06 Line-07
Taka
Sewing Lines
OT
NH3,063
1,049
5,467
191 -
1,000
2,000
3,000
4,000
5,000
6,000
Line-04 Line-05 Line-06 Line-07Ta
kaSewing Lines
Next Steps
1. ENTER & PROCESS DATA, “APPEND” TO BANGLADESH DATASET
2. ANALYSIS OF DATA AND SUPERVISOR SUVEYS
3. DESIGN OF INTERVENTIONS: Two main areas have been identified:
1. Information flows within firms 2. Quality upgrading