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

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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

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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)

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Taka

Sewing Lines

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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