department of engineering mangement center for …

Development of a Productivity Enhancement Framework for

Private Sector Automotive Manufacturing Industry of Pakistan

Author

Mr. Sheikh Zahoor Sarwar

UET Registration No 10-UET/PhD-CASE-EM-46

Supervisor

Dr Danial Saeed Pirzada

DEPARTMENT OF ENGINEERING MANGEMENT

CENTER FOR ADVANCED STUDIES IN ENGINEERING

UNIVERSITY OF ENGINEERING AND TECHNOLOGY

TAXILA

Development of a Productivity Enhancement Framework for

Private Sector Automotive Manufacturing Industry of Pakistan

A dissertation submitted in partial fulfillment of the degree of Doctor of Philosophy (PhD) in

Engineering Management

Author


UET Registration No 10-UET/PhD-CASE-EM-46 Approved by:

Dr. Danial Saeed

Pirzada

Thesis Supervisor

______________ _______________ __________________ Dr. Nadeem Ehsan Dr. Asim Nisar Dr. Amir Baqai

Member Research

Committee, EM

Department, CASE,

Islamabad

Member Research

Committee, EM

Department, CASE,

Islamabad

External Member

Associate Professor,

Mechanical Department,

NUST Rawalpindi

DEPARTMENT OF ENGINEERING MANGEMENT,

CENTER FOR ADVANCED STUDIES IN ENGINEERING,

UNIVERSITY OF ENGINEERING AND TECHNOLOGY, TAXILA.

I dedicate this research to my wife mrs. moneeza zahoor who

suffered a lot due to my busy schedule and commitments of the

study. This work is completed due to our combined sacrifices and

this success is ‘our’ success.

============

I am GREATLY indebted to my great parents, Mr. sheikh

Mohammad Sarwar and Mrs. shahzada parveen, for grooming

me into a better human being, a better Muslim and a better

Pakistani. You have been perfect and i exist because of you!

I

DECLARATION

It is declared that the matter of this thesis is the original work of the author and due

references and acknowledgements have been made, where necessary, to the work of

others. No part of this thesis has been already accepted for any degree, and it is not

being currently submitted in candidature of any degree.

_______________


UET Registration No. 10-UET/PhD-CASE-EM-46

Thesis Scholar

Countersigned:

______________

Dr. Danial Saeed Pirzada

Thesis Supervisor

II

ACKNOWLEDGEMENTS

I would like to acknowledge and thank my supervisor Dr. Danial Saeed Pirzada

for bearing with me for such a long time. It was owing to his guidance and deep

affection that I have been able to achieve this milestone of my life.

I would also like to thank all my teachers and mentors who polished me to

become a successful scholar. Special thanks to the faculty and staff of Center

for Advance Studies in Engineering and University of Engineering and

Technology, Taxila, who helped and guided me throughout this process. My

special thanks to Mr. Shahinshah Faisal Azeem and Mrs. Sadia Masroor for

helping and guiding me finalization of this thesis.

I would also like to thank the staff of Libraries of NUST, CASE, Punjab

University, UET Taxila and IST for always being there to provide me all the

help and support required for my literature review.

My special thanks to all the industry officials especially CEOs and Top

Management of the organizations, for giving me time to conduct interviews and

gather data for this research work.

III

ABSTRACT

Organizational productivity is one of the basic tools to gauge its competitiveness. Research has proven that

methodologies for gauging productivity are lacking in industries globally, and mostly non-standard tools

are used to measure and evaluate productivity. In Pakistan specifically, not enough efforts have been put in

place to gauge and enhance the productivity of manufacturing industry. This research is focused on

identifying the prevalent status of productivity in automotive industry of Pakistan and then suggesting a

productivity enhancement framework. This mixed methodology research has been conducted using both

qualitative and quantitative methods. Sequential explanatory design in combination with sequential

exploratory design was used as suggested by Creswell [106]. Quantitative research was conducted by

carrying out productivity analysis of the industry using secondary data from sample companies. Authentic

government sources, such as Engineering Development Board and two national level associations i.e.

Pakistan Automotive Manufacturers Association (PAMA) and Pakistan Association of Automotive Parts

and Accessories Manufacturers of Pakistan (PAAPAM) were consulted for data collection. Secondary data

for ten years covering FY 2000-2010 for two major automotive manufacturing firms was gathered.

Total Productivity and all partial productivities were computed using methodology proposed by Sumanth

[4], while Total Factor Productivity (TFP) was computed using Cobb-Douglas production function. Results

gathered showed low productivity status of the industry as compared to that of international industry. In

order to develop a productivity enhancement framework, qualitative research was conducted by collecting

primary data through qualitative interviews from top management of 26 automotive manufacturing

companies. A total of 40 interviews were conducted on the basis of theoretical saturation and theoretical

sampling. Open ended questions used for survey were compiled from the internationally published literature

for validity and reliability requirements. Using explanatory and descriptive study, role of technology in

productivity enhancement of the industry was examined.

Findings of this research have been used to develop a productivity enhancement framework for the industry.

Developed framework was compared with the framework of 6 different countries, including USA, UK,

Sweden, India, China and Thailand [33], [36], [37], [44], [45]. Comparison resulted in emergence of the

finalized productivity enhancement framework of the industry. This framework was then implemented in

one of the major auto parts manufacturing companies of Pakistan for its validation. Results of the

implementation not only validated the model but also depicted that there is an immediate need to implement

these concepts for productivity enhancement. The cost- effective solutions suggested in this model and its

cross cultural comparisons also show that this model can be used for manufacturing industries in general in

the developing countries.

Keywords— Productivity measurement, enhancement model, automotive industry, manufacturing.

IV

TABLE OF CONTENTS DECLARATION............................................................................................................................ I

ACKNOWLEDGEMENTS ......................................................................................................... II

ABSTRACT ................................................................................................................................. III

LIST OF TABLES ................................................................................................................... VIII

LIST OF ILLUSTRATIONS ..................................................................................................... IX

LIST OF ABBREVIATIONS ................................................................................................. XIII

CHAPTER 1 .................................................................................................................................. 1

INTRODUCTION & PROBLEM STATEMENT ..................................................................... 1

1.1 Background ...................................................................................................................... 1

1.1.1 Role of Productivity in Global Competitiveness ...................................................... 1

1.1.2 New Dimensions and Challenges to Productivity .................................................... 2

1.1.3 Automotive Industry and Productivity ..................................................................... 4

1.1.4 Pakistan Automotive Industry .................................................................................. 7

1.2 Philosophical Background................................................................................................ 9

1.3 Research Problem ........................................................................................................... 10

1.4 Motivation of Research .................................................................................................. 11

1.5 Scope of Research .......................................................................................................... 11

1.6 Objectives of Research ................................................................................................... 11

1.6.1 Main Objective of the Research ............................................................................. 11

1.6.2 Sub Objectives of the Research .............................................................................. 12

1.7 Intended Stakeholders and Significance of the Study .................................................... 13

CHAPTER 2 ................................................................................................................................ 15

LITERATURE REVIEW .......................................................................................................... 15

2.1 Significance of Productivity ........................................................................................... 15

2.2 Productivity Definitions and Measurement.................................................................... 15

2.3 Productivity Improvement Models and Issues ............................................................... 17

2.4 Productivity Enhancement in Automotive Industry ....................................................... 22

2.5 Role of Government and Productivity Issues in Developing Countries ........................ 22

2.6 Reasons for Selecting Pakistan and Gap in Literature Review ...................................... 23

2.7 Contextualization of Research ....................................................................................... 25

2.8 Factors Affecting Productivity ....................................................................................... 26

2.8.1 Role of Technology ................................................................................................ 26

2.8.2 Impact of Job Satisfaction ...................................................................................... 32

V

CHAPTER 3 ................................................................................................................................ 35

RESEARCH METHODOLOGY .............................................................................................. 35

3.1 Preface ............................................................................................................................ 35

3.2 Research Process ............................................................................................................ 37

3.2.1 Stage I Productivity Measurement using Quantitative Methodology ............... 37

3.2.2 Stage II Developing Productivity Enhancement Model using Qualitative Research

................................................................................................................................ 42

3.2.3 Stage III Implementation of the Proposed Framework ........................................ 44

3.2.4 Stage IV- Validation of model by Quantitative Analysis ....................................... 44

CHAPTER 4 ................................................................................................................................ 47

RESULTS OF QUANTITATIVE ANALYSIS: MEASURING PRODUCTIVITY ............. 47

4.1 Profit and Loss Statements Analysis .............................................................................. 47

4.2 Production Capacity Vs Productions Output Analysis .................................................. 48

4.3 Results of Productivity Analysis of the two firms under study...................................... 49

4.4 Measuring Productivity with Cobb-Douglas Production Function ................................ 54

CHAPTER 5 ................................................................................................................................ 58

RESULTS OF QUALITATIVE ANALYSIS ........................................................................... 58

5.1 Demographic Details ...................................................................................................... 58

5.2 State of Productivity Knowledge ................................................................................... 61

5.3 Coding of the Survey Responses .................................................................................... 67

5.4 Prevailing Best Practices in the Industry........................................................................ 72

CHAPTER 6 ................................................................................................................................ 82

DEVELOPMENT OF PRODUCTIVITY ENHANCEMENT FRAMEWORK................... 82

6.1 Exploring the Data ......................................................................................................... 82

6.2 Model of Prevailing Productivity Enhancement Practices in Pakistan Automotive

Industry .......................................................................................................................... 92

6.3 Model of Best Suitable Practices for Pakistan Automotive Industry ............................. 94

6.4 Model of Problems Faced in Implementation of Latest Techniques ............................. 96

6.5 Model of Future Planning for Productivity Enhancement by the Respondents ............. 98

6.6 Comparison with the World Best Practices and Models .............................................. 100

6.6.1 UK Productivity Enhancement Techniques ......................................................... 100

6.6.2 Swedish Productivity Enhancement Factors ........................................................ 101

6.6.3 USA Best Practices Implementation Model ......................................................... 102

6.6.4 Chinese Productivity Model ................................................................................. 103

6.6.5 Indian Manufacturing Improvement Strategies .................................................... 103

VI

6.6.6 Thai Improvement Model ..................................................................................... 105

6.6.7 Thai Technology Implementation Model ............................................................. 105

6.6.8 Strategic Productivity Improvement Framework ................................................. 107

6.7 Proposed Productivity Enhancement Framework for Pakistan Automotive Industry . 108

6.7.1 Human Resource Development (HRD) ................................................................ 112

6.7.2 Modified lean manufacturing (JIT) and optimization techniques ........................ 112

6.7.3 Total Quality Management (TQM) ...................................................................... 116

6.7.4 Agile Manufacturing ............................................................................................ 116

6.7.5 Enterprise Resource Planning (ERP) and Supply Chain Management system

(SCM) ................................................................................................................... 118

6.7.6 Total Productive Maintenance (TPM) .................................................................. 119

6.7.7 Total Productivity Management (TPmgt) ............................................................ 119

6.7.8 Computer Aided Design (CAD) and Computer Aided Manufacturing (CAD) ... 119

6.7.9 Partial Automation and Induction of Latest Equipment ....................................... 120

6.7.10 Energy Audits ....................................................................................................... 121

6.7.11 TRIZ ..................................................................................................................... 121

6.7.12 Autonomous Development ................................................................................... 122

CHAPTER 7 .............................................................................................................................. 124

IMPLEMENTATION METHODOLOGY ............................................................................ 124

7.1 Stage wise Implementation .......................................................................................... 124

7.2 Human Resource Development .................................................................................... 125

7.2.1 Methodology of Engineer’s induction and placement in an organization ............ 126

7.2.2 Training ................................................................................................................ 129

7.3 Modified JIT and Optimization Techniques ................................................................ 130

7.4 TQM Implementation ................................................................................................... 140

7.5 Agile Manufacturing .................................................................................................... 142

7.6 ERP and SCM Implementations .................................................................................. 145

7.7 TPM and TPgmt Implementation ................................................................................. 145

7.8 TRIZ and Autonomous Development Implementation ................................................ 146

7.9 Energy Audits ............................................................................................................... 150

CHAPTER 8 .............................................................................................................................. 152

VALIDATION OF PRODUCTIVITY ENHANCEMENT MODEL AND DISCUSSION OF

THE OUTCOMES .................................................................................................................... 152

8.1 Production Graphs ........................................................................................................ 153

8.2 Human Resource Savings............................................................................................. 159

VII

8.3 KAIZEN’s Achieved .................................................................................................... 161

8.4 Development Projects .................................................................................................. 169

8.5 Energy Audit Results ................................................................................................... 173

8.6 Results in Financial Terms ........................................................................................... 178

8.7 Conclusions & Recommendations ............................................................................... 180

REFERENCES .......................................................................................................................... 188

ANNEXURE A .......................................................................................................................... 201

ANNEXURE B .......................................................................................................................... 204

ANNEXURE C .......................................................................................................................... 205

CURRICULUM VITAE ........................................................................................................... 207

PUBLICATIONS ...................................................................................................................... 208

UNDERTAKING ...................................................................................................................... 211

SUPERVISOR’S COMMENTS .............................................................................................. 212

VIII

LIST OF TABLES

Table No Table Caption Page No

Table 4.1 Toyota and Honda correlation values 55

Table 4.2 Descriptive statistics 56

Table 4.3 Unstandardized coefficients of regression 56

Table 5.1 Responses about productivity terminology with demographics 63-64

Table 5.2 Responses regarding productivity measurement methods used in

these organizations

66

Table 5.3 Summary of the all the words used with count and weighted

percentage

70

Table 7.1 Activity Based Costing example of one of the component 144

Table 8.1 Detail of Salary and Employees from Jan-2010 to Dec-2012 160

Table 8.2 KAIZEN’s In One Year 162-168

Table 8.3 Parts developed in a short span of ten months due to Autonomous

Development Implementation

170-172

Table 8.4 List of motors used on one section with their cost effect 174

Table 8.5 Replacement of motors with cost effect 175

Table 8.6 Difference in Revenues from 2010 to 2012 after implementation of

the Model

179

IX

LIST OF ILLUSTRATIONS

Figure No Figure Caption Page No

Figure 1.1 Production pattern of automotive industry in the world, region wise 5

Figure 1.2 Global automotive production region wise from 1999 to 2012 6

Figure 1.3 Production pattern of automotive industry in the world, region wise 6

Figure 1.4 Trend line of Auto industry showing huge growth in production 8

Figure 1.5 Showing trend line of total production of the industry for both

commercial CV and private vehicles PV

8

Figure 1.6 Report of Federal Bureau of Statistics (FBS) Pakistan 2011 9

Figure 2.1 PPP Model as suggested by Tangen (2005) 21

Figure 2.2 Contextualization of research 25

Figure 4.1 Profit and Loss status of Indus Motors and Honda Atlas (Financial

Statement)

48

Figure 4.2 Line graph showing production trend line of Indus and Honda

Motors

49

Figure 4.3 Honda and Toyota Capacity verses Output 50

Figure 4.4 Comparison of partial productivities of Honda and Toyota 52

Figure 4.5 Total Productivities of Honda Atlas and Indus Motors 53

Figure 4.6 Total Productivities Indices of Honda Atlas and Indus Motors 53

Figure 5.1 Graph regarding number of respondents’ designation wise 59

Figure 5.2 Graph between designation and qualification 59

Figure 5.3 Graph of Age of the respondents 60

Figure 5.4 Graph between Designation and Age 61

Figure 5.5 Responses about terminology “Productivity”, yes for correct and no

for wrong meanings

62

Figure 5.6 Responses %age to correct and wrong measurement methods 67

X

Figure 5.7 Word tree for text run query search of word “Wastage” 69

Figure 5.8 Word tree for text query search of word “Kaizen” 69

Figure 5.9 Tag Cloud results the words and terminologies which have been

more emphasized by the respondents are shown in bigger size font

71

Figure 5.10 Graph showing 65% agree that tacit knowledge is very important

and 35% disagree

80

Figure 5.11 Graph showing 92.5% disagree that unions are good for productivity

and 7.5 % agree with this statement

80

Figure 6.1 Screen shot displaying formation of tree nodes 83

Figure 6.2 Coding strips showing the coding details and the density of the

coding

85

Figure 6.3 Node map showing the categories and sub categories with color

schemes

86

Figure 6.4 Results of Matrix coding query showing the numbers of responses

on optimization from people of different designation

88

Figure 6.5 Results of group coding query as connection map for respondents

vs used productivity enhancement practices

90

Figure 6.6 Zoom in view for Figure 6.5 showing the prominent concept 90

Figure 6.7 Connection Map for problems faced in implementation of latest

tools and techniques

91

Figure 6.8 Zoom in view of Figure 6.7 showing three major emerging themes 91

Figure 6.9 Zoom in view of Figure 6.7 showing Human resource resistance as

an emergent theme

92

Figure 6.10a Results of the model run test in NVIVO 93

Figure 6.10b Finally Developed Model of Prevailing Productivity Enhancement

Practices in Pakistan Automotive Industry

93

Figure 6.11 Suggested productivity enhancement model for Pakistan

automotive industry by the experts of the field

95

Figure 6.12 Model of problems faced in implementation of productivity

enhancement techniques

97

Figure 6.13 Model of future plans for productivity enhancement 99

Figure 6.14 Productivity enhancement model for UK manufacturing industry 100

Figure 6.15 Productivity Enhancement Factors by Thomas Grünberg (1996) 101

XI

Figure 6.16 USA best practices model 102

Figure 6.17 Chinese productivity enhancement techniques model 103

Figure 6.18 Indian automotive industry best practices model 104

Figure 6.19 Top 10 best practices of Thai automotive industry 105

Figure 6.20 Thailand top 15 automotive improvement techniques model 106

Figure 6.21 Problems faced in implementation of latest techniques in Thailand

automotive industry

106

Figure 6.22 Productivity improvement strategies framework of McTavish et al

(1996)

107

Figure 6.23 Productivity Enhancement Framework for Pakistan Automotive

Industry

111

Figure 7.1 Old Layout of Manufacturing sections 134-135

Figure 7.2 New layout of Manufacturing CNC section with latest techniques

used

138

Figure 7.3 Zoom in of flywheel production line and brake disc line 139

Figure 7.4 Zoom in for Brake drums manufacturing cell showing the process

flow with the help of arrows.

139

Figure 8.1 Production graphs of brake disc from Jan 2010 to Mar 2012

showing 396% production increase on same machines and lesser

manpower

154

Figure 8.2 Production graph of Brake Drum from Jan 2010 to Mar 2012

showing a production increase of 374% on same machines with

lesser manpower

154



lesser manpower

156



lesser manpower

156

Figure 8.5 Production graph of Valve Chamber from Jan 2010 to Mar 2012

showing a production increase of 652% with very less financial

investment

158

Figure 8.6 Graphs of three years lines showing number of employees per

month

160

XII

Figure 8.7 Comparison of energy consumption before and after the project

with indication of actual power required in green color

176

Figure 8.8 Financial effect of energy consumption before the project, after

project and price saving

177

Figure 8.9 Power consumption difference before and after project and power

saving

177

XIII

LIST OF ABBREVIATIONS

ABC Activity Based Costing

AMT Advanced Manufacturing

Technologies

AD Autonomous Development

BOK Body of Knowledge

BPR Business Process Reengineering

CAD Computer Aided Design

CAM Computer Aided Manufacturing

CAQDAS Computer Aided Qualitative

Data Analysis

CAR Center for Automotive Research

CEO Chief Executive Officer

CFR Credit Research Foundation

CNC Computerized Numerical Control

CMM Coordinate Measuring Machine

COO Chief Operations Officer

CIM Computer Integrated

Manufacturing

ECA Ethnographic Content Analysis

EDB Engineering Development Board

EK Explicit Knowledge

ERP Enterprise Resource Planning

FBS Federal Bureau of Statistics

FDI Foreign Direct Investment

FMEA Failure Mode Effect Analysis

FMS Flexible Manufacturing System

FY Financial Year

GDP Gross Domestic Product

GM General Manager

HRD Human Resource Development

IPO International Productivity

Organization

IT Information Technology

JIT Just in Time

JS Job Satisfaction

KTP Knowledge Transfer Partnership

LOS Length of Service

MOIP Ministry of Industries and

Production of Pakistan

OEM Original Equipment

Manufacturers

OPT Optimized Production

Technology

OICA Organisation Internationale

des Constructeurs

d'Automobiles

PAMA Pakistan Automotive

Manufacturers Association

PAAPAM Pakistan Association of

Automotive Parts and

Accessories Manufacturers of

Pakistan

PDCA Plan, Do, Check and Act

PEOU Perceived Ease of Use

PLS Profit and Loss Statement

PMMI Performance Management,

Measurement & Information

PPC Production and Planning Cell

PPP Model Productivity, Profit and

Performance Model

PSMCL Pakistan Suzuki Motors

Corporation Limited

PU Perceived Usefulness

QA Quality Assurance

QFD Quality Function

Development

R&D Research and Development

SCM Supply Chain Management

SECP Securities and Exchange

Commission of Pakistan

SME’s Small and Medium

Enterprises

TAM Technology Acceptance

Model

TFP Total Factor Productivity

TK Tacit Knowledge

TOC Theory of Constraints

TQM Total Quality Management

TPmgt Total Productivity

Management

TPM Total Preventive Maintenance

TPS Toyota production system

TRIZ Theory of Solution of

Inventive problems

ZI Zero Inventory

Chapter 1- Introduction

1

CHAPTER 1

INTRODUCTION & PROBLEM STATEMENT

1.1 Background

1.1.1 Role of Productivity in Global Competitiveness

In the early nineteenth century, the governing factors of influence were feudalism,

imperialism and regional power struggle [1]. In the mid-nineteenth century, agricultural production

became the center of attention and the world entered the “agricultural era”. In this era, intelligentsia

and practitioners concentrated on developing of methodologies for agricultural growth. The later

part of nineteenth century and early twentieth century is known as the “industrial era” wherein

ability to enhance manufacturing productivity became the biggest line of demarcation and

distinction between the nations, owing to which the world got segregated into industrialized and

non-industrialized states. All efforts of development in this era focused on this very aspect of

manufacturing productivity. In the mid twentieth century, the world entered into a new era called

the “technology era”. All the advancements in the former eras have helped in developing

technologies, which have ultimately changed human lives. In the technology era, the world has

been differentiated between those who have the technological capability, are able to further

enhance technical knowledge and know-how and can simultaneously employ the same for the

advantage of mankind vis a vis those who don’t have these capabilities and knowledge [1].

Technological advancements have brought revolutionary changes in the past few decades.

New techniques and technologies have emerged in every field of life. New inventions have

enhanced the need to revise and upgrade frequently used methodologies and definitions of terms

used in various fields. Globalization has changed concepts related to competition. With the

expansion of businesses and interdependence of economy, geographical boundaries are no longer

a limit. The whole world has become a common market. Anyone regardless of origin can come


2

into the field of competition. Productivity* is generally used as a measure of competitiveness [2],

[3]. In order to remain competitive in the global market, companies and firm s are striving for

higher standards of productivity.

With changing scenarios, methodologies used for measuring productivity and even

defining productivity require more thorough research and studies [4]. In the past few decades a lot

of research studies have been conducted on productivity all over the world [4]–[18]. Unfortunately,

in Pakistan not enough efforts have been placed to describe and gauge industrial productivity,

especially that of manufacturing industry [19]. In most of the research conducted on the issue, a

few major factors affecting productivity of an industrial organization have been highlighted,

including technology (being the most deliberated upon factor), equipment, management,

personnel, job satisfaction, rules and procedures [5], [6], [17].

1.1.2 New Dimensions and Challenges to Productivity

The 21st century has taken us into an entirely new technological era. With the emergence

of new technologies, people remain connected to their office work even when they are away from

their work place†. These new dimensions of work gave rise to numerous controversies e.g.

calculation of inputs (especially in time) and outputs (service/knowledge work). Furthermore, in

these changing scenarios, several difficulties are being faced in defining and measuring

productivity, which pose a major challenge for researchers. In order to measure productivity, the

use of partial productivities is generally resorted to, but they cannot depict the complete picture‡.

Therefore, measuring “Total Productivity” was proposed by Sumanth [4]. Several industrial

* Productivity is the term first used by Quensey in 1766 about 200 years ago as reported by Sumanth (1997). Since

then different definitions of the term have been suggested. The Organization of European Economic Cooperation

OEEC (1950) defined productivity as “Quotient obtained by dividing output by one of the factors of production”. † Work connectivity behavior of employees while being away from the workplace has been studied worldwide posing

new challenges for the researchers as well as for the industry. ‡ Sumanth (1994) elaborated upon the limitations of partial productivities. In the field of Economics several other

methods for measuring productivity like Cobb Douglas Production functions are used to overcome these limitations.


3

surveys in different countries have reported that basic standard methodologies are not in use to

measure and evaluate productivity; rather, nonstandard tools are being used for the purpose [4],

[10], [20]. The major reason is that knowledge and concept of productivity is misunderstood. The

drawback of nonstandard tools is that the time factor is not considered in these methodologies. The

time factor is very important in defining when a profit earning activity will achieve its desired

output or a specific government policy will render its effectiveness in terms of benefit for citizens

and nations.

Productivity analyses-based research on industries and organizations have picked up pace

all over the world in recent times. Main objectives of these research works have been to indicate

the flaws and suggest remedial measures. In a detailed analysis of manufacturing industries in

India [21], the researcher indicated the efficiency-gap between foreign and domestic firms in

eleven manufacturing industries. Hossler et al. [11] indicated the effectiveness of model techniques

for significant productivity enhancement. Researchers studied the necessity of model-to-model

transformations and successfully implemented the same, showing momentous productivity

enhancement. Credit Research Foundation (CFR) formulated a Collection Productivity formula;

which carries out productivity analyses to guide industries how to enhance their productivity. All

these latest research shows the interest of both academia and industry to find the solution to the

issues of productivity enhancement [4], [22]–[29]. However, further research is required in

different fields to identify the productivity problem areas and suggest enhancement methodologies

for industry. Several productivity enhancement models have been proposed in the past, but they

all focused on performance enhancement rather than productivity§. In Pakistan, especially in the

automotive manufacturing industry, comprehensive research has not been found despite extensive

§ This gap in the Body of Knowledge has been explained and discussed in detail in para 2.3 of Chapter 2.


4

literature review. So there is a dire need to carry out a comprehensive productivity measurement

of this industry; and on the basis of the findings suggest productivity enhancement framework.

1.1.3 Automotive Industry and Productivity

Economic growth of a nation depends upon its major industries. In the recent past, the

automotive industry has been recognized as a major contributor of growth, technology,

employment and GDP in many countries [30]. In today’s globally competitive world, the

automotive industry has to face enormous challenges such as e hyper-competition, adoption of

latest and advanced production technologies, meeting strict safety requirements, and enhanced

environment protection laws [31], [32]. Due to the importance of the role played by automotive

industry in the economic growth and development of a country, a lot of research has been

conducted in different countries on this industry [33]–[38]

Several analyses conducted on automotive industry status globally have identified that

there has been a great shift in productions and sales of automotive products. Figure 1.1 depicts an

analysis by Center for Automotive Research [39]. The graph shows that since 1999 to 2005,

production of automotive industry in America has declined gradually from 34% in 1999 to 24% in

2005. Similarly automotive production has declined in Europe from 35% in 1999 to 31% in 2005.

However, production in Asia has enhanced from 30% in 1999 to 37% in 2005. In another statistical

analysis performed by Kanoema [40], similar kind of findings had been reported. Results as shown

in Figure 1.2 depict that automotive production in America and Europe has declined while it has

seen a gradual increase in Asia region**. As far as Asia is concerned, apart from Malaysia and

** Growth of auto industry in Asia is not surprising as most of the manufacturing industry of the world has shifted to

this region. The main reason behind this shift is that huge human resource is available in this area and also on very

minimal rates than any other region of the world.


5

Figure 1.1. Production Pattern of Automotive Industry in the World, Region- wise

Source Center for Automotive Research [39]

Indonesia the countries that have shown increase in production are India, China and Pakistan.

Another research conducted [39] has shown a detailed breakdown of the region-wise trends in

global vehicle production. The results as shown in Figure 1.3 depicts that major production of

automotive manufacturing has shifted towards South Asia. China holds a major portion in this

production chart. The most important aspect to be noted from all the research is that automotive

trend had shifted towards the Asia region, with China on top of the list in world automotive

production in numbers; however, neighboring countries of China including India and Pakistan are

also flourishing in this industry. The main reason of this increase is comparatively cheap workforce

in this region owing to which, there is a huge potential for this industry to grow further. As per

rankings provided by [41], China is on top of the list, India is at number 6, while Pakistan is way

down on 35th position. For better growth of this industry in Pakistan there is a dire need to

benchmark the best practices followed especially in China and India.


6

Figure 1.2 Global Automotive Production Region Wise from 1999 to 2012

Source Kanoema [40]

Figure 1.3 Production Pattern of Automotive Industry in the World, Region Wise

Source Center for Automotive Research [39]


7

1.1.4 Pakistan Automotive Industry

Pakistan is one of the developing countries having remarkable potential of manufacturing

enhancement. Pakistan entered the race of productivity enhancement a bit late. The automotive

industry of Pakistan has shown some improvements mainly owing to enhanced capital inputs,

though its contribution in GDP and employment is still modest in size††. From this perspective, a

remarkable difference can be observed if compared with other Asian countries like Japan, Korea,

Malaysia, India, China and Thailand. In all these countries the automotive industry has exploited

the catalytic role in promoting broad based manufacturing sector growth [42]. However, not much

research has been carried out on the operational procedures and productivity enhancement

possibilities of this industry [19].

The production status of complete automotive industry of Pakistan has been analyzed by

different organizations. These analyses have shown that there has been a great increase in the

production of this industry. The significant growth in the last decade as shown in Figure 1.4 depicts

that there is a great potential in this industry as far as Pakistan is concerned. Another survey

conducted by Indus Motors shows the production trend line of the Pakistan automotive industry

over a span of five years, from FY 2005 to 2010. Results are shown in Figure 1.5. It shows that

production levels dropped in FY 2007-08, while FY 2008-09 was the worst year for the whole

automotive industry. However, FY 2009-10 showed an improvement upon the otherwise declining

trend. In 2011, the Federal Bureau of Statistics (FBS), Pakistan reported that automobiles

manufacturing industry is producing more than any other industry in Pakistan (results shown in

Figure 1.6).

†† Pakistan GDP growth rate has been very low as compared to the GDP rate four to five decades ago. Contribution

of manufacturing industry in Pakistan GDP had been fluctuating around 18% to 19% in past few years. However, this

industry has the potential to make a better contribution in GDP.


8

Figure 1.4 Trend Line of Auto Industry Showing Huge Growth in Production

(Source Pakistan Association of Automotive Parts and Accessories Manufacturers

of Pakistan (PAAPAM)

Figure 1.5 Showing Trend Line of Total Production of the Industry for Both

Commercial (CV) and Private Vehicles PV (Toyota 2009)


9

Figure 1.6 Report of Federal Bureau of Statistics (FBS) Pakistan

These statistics specifically show that by incorporating productivity enhancement practices in this

industry, the GDP of the country can further be improved.

1.2 Philosophical Background

According to the latest research, there is no single methodology which can give a perfect

solution for productivity enhancement. Harrington [43] discussed the confusion of management

on choosing technology to attain higher benefits. This research has focused on the need to develop

customized solutions for different industries. McTavish et al. [44] discussed different management

techniques and manufacturing technologies and suggested that customized solutions for different

industries are required. Grünberg [23] carried out a detailed historical review of improvement

methods in manufacturing operations from 1776 to date. It was pointed out that most of the

techniques once used in one type of settings proved unsuccessful in the other type of setting

(eastern setting or western setting). Since all these techniques are too general as they come from

different fields, hence there is always a need to specify as to which technologies are most effective


10

for different industries. In the light of these findings and in view of the fact that the role of

automotive manufacturing industry in GDP growth of a country is well recognized, several

productivity enhancement models have been researched upon and proposed for the automotive

industry of different countries. The model and frameworks have been developed for several

countries like USA [33], United Kingdom [45], Sweden [22], China [37], India and Thailand [36].

However, despite extensive research, the researcher could not find productivity enhancement

framework of prevailing productivity enhancement practices of the Pakistani automotive industry.

Hence, a dire need was felt to conduct extensive research to find out the prevailing practices of the

Pakistani automotive industry and suggest the best practices’ framework most suitable for the

industry.

1.3 Research Problem

Existing Body of Knowledge (BOK) lacks to identify the prevailing productivity status of

Pakistan automotive manufacturing industry. The prevailing best practices of the industry were

not enumerated and problems faced in implementation of the latest techniques were not well-

known. Considering this scenario the research problem targeted was to identify the prevailing

productivity status of this industry, enumerate the best practices followed in this industry and

highlight the problem faced in implementation of the latest techniques in order to give a

comprehensive solution to the industry. To address the issues, this research was conducted by

performing productivity analysis of the industry, detailed interviews were conducted to enumerate

the prevailing best practices and results were compared with the best practices of the world.

Suggested finalized framework of the study was tested in real industrial settings to prove the

usefulness of the solution provided.


11

1.4 Motivation of Research

A lot of productivity enhancement solutions have been suggested such as Goodwin’s model

[46], Sutermeister’s model [47], Hershauer and Rcuh’s model [48], Crandall and Wooton’s

strategies [49], Stewart’s strategy [50], Analytical productivity improvement model [51],

Productivity improvement strategy [44] and Total Productivity Management (TPmgt) by [4].

However instead of productivity, performance was identified as the desired outcome in all these

models and this aspect was identified by researchers all around the world [4], [23], [25]–[27], [29],

[52], [53]. Especially after the acceptance of PPP Model proposed by Tangen [27] which

highlighted that productivity is at the core of performance and productivity umbrella, research

started in different countries of the world to find a solution for productivity enhancement of the

respective industries. Considering all these aspects, the researcher was motivated to develop a

framework which can focus on productivity enhancement for Pakistan automotive industry.

1.5 Scope of Research

Scope of this research is (but not limited to) to identify the prevailing productivity status

of Pakistan automotive manufacturing industry. This research also highlights the prevailing best

practices of the industry as well as the problems faced in implementation of the latest techniques

and technologies and suggest the most suitable best practices for this industry. Methodology of

implementation of these technologies and practices has also been suggested. The proposed

framework has been implemented in one of the major auto parts manufacturing company of

Pakistan and the results attained for productivity enhancement have also been elaborated.

1.6 Objectives of Research

1.6.1 Main Objective of the Research

Main objective of this research is to develop a productivity enhancement framework for

the private sector automotive manufacturing industry of Pakistan.


12

1.6.2 Sub Objectives of the Research

Sub objectives of research are (but not limited to) as under:

One of the sub objectives of the research is to identify the prevalent condition of

productivity in automotive industry of Pakistan by focusing on measurement of

productivity in major automotive manufacturing companies of Pakistan.

Productivity measurements will indicate the main productivity flaws of automotive

industry by pointing out the resources which have not been utilized to their

optimum. This measurement will indicate the probable productivity enhancement

areas.

Explore the extent of Productivity knowledge in the industry and productivity

practices.

To determine the prevailing best practices adopted in the industry.

To identify the main barriers posed in implementation of latest techniques and

practices.

Benchmarking best practices adopted by the automotive manufacturing industry

globally and comparing the best practices of the industry most closely associated

with Pakistan environment to suggest the framework.

To give a comprehensive methodology for adoption of this productivity

enhancement framework.

To validate the model by actually implementing the framework in one of the

companies of the industry.


13

1.7 Intended Stakeholders and Significance of the Study

Considering the research problem in hand, a unique approach was used to conduct this

study. Firstly, the present situation of the industry was analyzed. Then after taking input from the

stake holders a framework was generated, which was then compared with the best models of the

world. This comparison resulted in developing the finalized suggested framework. The final

recommendations of the framework were implemented in a functional company. The remarkable

financial and operation gains achieved due to these steps indicate the originality and

purposefulness of the research. This research will be beneficial for all the following stakeholders:-

All automotive manufacturing companies of Pakistan that intend to and are willing to

enhance their productivity and ultimately their profits.

All automotive manufacturing companies of developing countries (with minor

modifications) as the proposed framework are suitable for similar settings.

All manufacturing companies of Pakistan and other developing countries (with minor

modifications), as the proposed framework has been tested for validity through on

ground verification and the generalizability of the findings have been confirmed by

cross- cultural comparison.

Government bodies for making policies and rules for the industry.

All the governing bodies of the industry like Engineering Development Board of

Pakistan (EDB) for setting standards and redefining policies.

PAAPAM and PAMA for enhancing the productivity of this industry.

Consultancy and training firms that provide services to this industry.

Foreign investors and multinational firms who have invested or are considering

investments in the Pakistan automotive industry.


14

Chapter Summary

Technological advancements have brought revolutionary changes in the past few decades.

Mass globalization has changed the world and the concepts related to competition have also

transformed. Productivity, which is one of the key measure of competitiveness has become center

of focus for many research works conducted around the globe. New dimensions and challenges

have emerged in the field of productivity from defining and measuring to productivity

enhancement. Automotive industry is playing a vital role in GDPs of several countries. In past few

years there has been a major shift in number of automobiles produced and sold from western

countries to eastern countries. Production and sales of automotive in Pakistan has also increased

manifolds. In order to remain competitive with the world Pakistan automotive industry has to focus

on productivity enhancement. Existing Body of Knowledge (BOK) lacks to identify the prevailing

productivity status of Pakistan automotive manufacturing industry. Considering this scenario this

research focused on identifying the prevailing productivity status of this industry, enumerate the

best practices followed in this industry and highlight the problem faced in implementation of the

latest techniques in order to give a comprehensive solution to the industry for productivity

enhancement.

Chapter 2- Literature Review

15

CHAPTER 2

LITERATURE REVIEW

2.1 Significance of Productivity

The expansion of international trade, globalization of economies and emergence of new

markets have made productivity a critical success factor for any country in the world. Anticipating

these developments, most of the countries have formulated strategies and policies to ensure that

their local organizations have the capability to compete in the global market. Productivity is

generally used as a “measure of competitiveness” [2]. Problem faced in developing countries is

not only underdevelopment but also that of mis-management* [1]. Numerous studies have been

conducted to find out management issues; such as, determining the relationship of job behaviors

of employees, job satisfaction and motivation with employee commitment, turnover, absenteeism,

productivity and occupational stress [54]–[58]. Productivity has been identified as one of the most

serious challenges that have been confronting management. Apart from higher profitability and

better performance [27] productivity has been found to be negatively related with inflation. It is

positively related with the enhanced quality of life, higher employment rate, political stability and

economic growth of the country [1], [4].

2.2 Productivity Definitions and Measurement

Productivity and production are terminologies which have been misused and

misunderstood by many. Since the first mention of the word productivity by Quensey in 1766 [4]

several different definitions of the term have been suggested. The Organization of European

Economic Cooperation OEEC (1950) defined productivity as “Quotient obtained by dividing

* Todaro and Smith (2008) indicated in their book “Economic Development” at page 6 that in developing countries

issues of low productivity and poor performance are more related to management flaws rather than other techniques

and technologies used. They have further highlighted these issues in the proceeding chapters.


16

output by one of the factors of production”. In defining productivity difference of objectives of

different stakeholders is the major issue. The reason of this difference is that the objectives of firms

and nation are multidimensional. The objectives of government are focused on improving the

standard of living of its citizens, increase employment and create more jobs. The main aims of the

firms are focused towards winning market shares both domestically and internationally, enhance

profits, and compete globally.

Sumanth [4] differentiated productivity and production† and explained that “production is

concerned with the activity of producing goods and/or services”, whereas, “productivity is

concerned with efficient and effective utilization of resources (inputs) in producing goods and/or

services (output)”. The author further distinguished partial productivity, total factor productivity

(TFP), total productivity and total productivity management (TPMgt)‡. He defined Partial

productivity as “ratio of gross output to single factor input”. Total factor productivity was defined

as “ratio of net output (excluding materials from gross output) and the sum of labor and capital

inputs in deflated monetary units”. Total productivity was defined as “ratio of total output to the

sum of all input factors”. Despite clear theoretical demarcation, practical implementation of these

terminologies in industrial applications has remained a grey area. Heshmati [59], [60] studied the

core methods of measuring efficiency and productivity. The author elaborated upon the effects of

productivity growth and efficiency in manufacturing and service industries. In another study the

† It has been reported by several researchers that in industry people used production and productivity

interchangeably. This misconception caused several issues related to the enhancing efficiency and effectiveness.

Sumanth in his books Productivity awareness in the US: A survey of some major corporations (1980) pages 84-90,

and Productivity Engineering and Management (1994), deliberated upon this aspect and clarified these terms. He

also identified that the knowledge of productivity is very vague even in the industry of developed countries like

USA as well. ‡ Sumanth in his book Total Productivity Management, A systematic and quantitative approach to compete in

quality, price and time (1998) gave the concept of Total Productivity Management Chapter 4. He gave the complete

system of measuring, evaluating, planning and enhancing productivity.


17

latest trends of these methods were compared [60]. Wang and Szirmai [18] carried out a

comprehensive study on the Chinese manufacturing industry. They studied the productivity growth

of this sector from 1980 to 2002. The study deliberated upon the structural changes in the sector

as well as the effects of productivity growth.

Another myth argued about by many researchers is that productivity and quality don’t go

hand in hand [9], [10], [61]. It has been reported that this misconception prevails in several large

industries like the Finnish Industry [9] and also the American industry [61]. Hunnula [10] indicated

that this myth is true only if partial productivity ratios are utilized. The author gave a solution that

this problem can be solved by using Total productivity measures, since conceptually total

productivity measures incorporate only quality products in the outputs. Author further suggested

and proved that total productivity can be measured with the help of simple and commonly used

partial productivity ratios. He named this methodology as expedient total productivity

measurement. This methodology helps the firms to effectively measure and thus enhance their

productivity. Furthermore, Cobb-Douglas type production functions are preferred from point of

view of economists but are not generally used in managerial practices due to complexities involved

[10]. In this research Cobb-Douglas production function has been used to determine the factors of

productivity and to calculate total factor productivity.

2.3 Productivity Improvement Models and Issues

For productivity enhancement at firm and international level several models have been

proposed. Goodwin [46] gave a productivity enhancement model named as “Goodwin Model”.

The main theme of this model was “Improvement Management”. He emphasized that the way we

improve has to be improved first. He gave a three-prong approach encompassing philosophy of

human considerations, tools and techniques to be incorporated and the complete plan envisaging

a stream of actions to be conducted. His model was not focused on productivity improvement as


18

envisioned, rather it gave a complete framework for organizational change and performance

improvement.

Sutermeister’s approach [47], focused on labor productivity and performance. Schematic

diagram of his model comprised of series of circles with labor productivity and performance at the

core of the circles. He elaborated that the factors affecting labor productivity were arranged in

circles, those nearer to the circle of the core affects more the labor productivity than the ones

further away. His model consisted of two major themes; technological development and

employee’s motivation. He showed the interrelations of different factors affecting the employee’s

productivity and performance with the help of pictorial depiction. His model too was an

interpretation of taking productivity and performance collectively. Despite being fairly elaborative

his model was a broad descriptive framework to enhance labor productivity and performance.

Hershauer and Rcuh [48] gave a “Servo System Model”. This model was focused on worker

performance. They showed as to how organizational factors and individual factors affect the

worker performance directly or indirectly. They particularized this model as a “dynamic feedback

system”. This model was adopted and implemented by several organizations of the industry with

successful results. However, this model gave a system for performance improvement only the

worker. This model was considered to be a good system for qualitative feedback but was unable

to give any quantitative results for the industrialists to compare the performance.

Crandall and Wooton [49] explained in their research that the traditional efficiency based

productivity improvement models were to be replaced with organizational growth strategies. Their

proposed strategies known as “Crandall and Wooton’s Strategies” were focused on

“entrepreneurial growth”, “bureaucratic growth”, “diversification and systemization growth” and

“mega organizational growth”. The main themes of this model were “stabilization”,


19

“redevelopment” and “reduction”. These techniques were very realistic but these strategies again

focused on organizational performance instead of organizational productivity. They emphasized

that focus on organizational growth will ultimately result in productivity and efficiency

improvement of the organization. As their focal point was organizational growth and

organizational culture, so they expounded upon the issues of long term strategies, missing out the

daily improvement activities necessary for productivity growth.

Stewart [50] gave a more focused approach for productivity improvement. The

productivity enhancement model proposed by him is known as “Stewart’s Strategy”. Instead of

focusing on overall organizational performance improvement strategies, he proposed a system of

network encompassing small improvement from lower level in order to improve organizational

performance. His schematic diagram gave a system in which an organization is seen as a grid of

small subunits working together for enhanced organizational performance. He gave a detailed

approach in which small teams of a unit work in collaboration with the teams of other units for

improvement of the system. His concept of task force was very near to the quality circle teams as

given in TQM Philosophy. He used the Nominal Group Technique (NGT) for development of

several groups all around the organization for improvement from the grass root level. His model

was probably closest for industrial implementation. However, due to the complexities of the

model, it was not used widely in manufacturing units.

Aggarwal [62] gave a step by step procedure for productivity enhancement in

organizations. His procedure was based on several case studies carried out in industrial settings.

His procedure was named as “Aggarwal Approach”. His steps included; identification,

prioritization and quantification of the issues, preparation of action plans for productivity

improvements, elimination of productivity barriers in the industry, development of productivity


20

measurement model, execution of the productivity improvement plans, motivating workers and

staff, maintaining momentum of productivity efforts and continuous audit of the organizational

climate. His approach was one of the most focused approaches for productivity enhancement but

failed to get industrial application status. Despite being based on real time case studies this

approach failed to get industrial attention. It was more of a broad outline on productivity

improvement without elaborating the detail explanation of the methodology to be followed. For

industrialist it was more of an academic proposal rather than a feasible industrial implementation

model. Sumanth [51] utilized the findings of these studies and the step by step approach of

Aggarwal, and suggested an “Analytical Productivity Improvement Model”. Continuous efforts of

Sumanth, focused towards industrial application resulted in a better response from the industry.

He conducted several industry wide surveys and resultantly was able to come up with the most

accepted management technique known as Total Productivity Management (TPgmt) [4]. His

surveys focused on industry and ensured industrial officials to be part of these developments.

Resultantly, he was able to get better acceptance of his productivity management strategy by the

industry. He gave the steps of productivity measurement, productivity evaluation, productivity

planning and productivity improvement. His management strategy was largely adopted by industry

but lacked the sequence and details of the latest manufacturing technologies and diverse

management techniques. However, researchers all around the globe kept on striving to suggest

customized solutions for different industries.

One aspect to be noticed in these models is the fact that generally performance was

considered as the core desired outcome instead of productivity, assuming that higher productivity

would be achieved in the process. The terms productivity and performance are often confused and


21

incorrectly considered as mutually interchangeable, like the terms efficiency and effectiveness§.

Many researchers [4], [52], [53] believed that by referring to productivity people were actually

working on performance improvement. A similar myth prevailed regarding productivity and

profitability that they go hand in hand, so most of the organizations concentrated on profitability

and performance in financial terms rather than concentrating on productivity enhancement

techniques. Many researchers [23], [25], [27] indicated this myth and elaborated that these

terminologies must not be taken as similar. Tangen [27] gave the clear demarcation of productivity,

profitability and performance in PPP Model. In the triple-P model he explained the differences of

productivity, profitability and performance respectively as being a physical phenomenon,

monetary relationship and an umbrella term for both the former, for easy understanding, more

accurate measurements and enhancement attempts. His model as shown in Figure 2.1, elaborated

that productivity is at the center of the model which is a physical phenomenon. Profitability is a

monetary relationship and Performance is an organizational phenomenon which incorporates both

Figure 2.1 PPP Model as suggested by Tangen [27]

§ Effectiveness, efficiency and productivity terms are also not used with clear demarcation. Sumanth (1998)

differentiated that effectiveness is getting the job done in a given specific time, efficiency is getting the job done with

minimum possible resources in a given specific time. Whereas productivity is the ratio of output and input.


22

productivity and profitability. He further distended the necessity of tackling these terms separately

in order to have a more focused measurement and enhancement endeavors. After this demarcation,

a lot of research has been carried out all around the globe. It aided in the development of

improvement methodologies specifically for productivity enhancement [25], [28], [38], [63].

2.4 Productivity Enhancement in Automotive Industry

In the recent past the automotive industry in many countries has been recognized as a major

contributor of growth, technology, employment and GDP [30]. Owing to the importance of the

role played by this industry in the economic growth and development of a country, a lot of research

has been conducted all over the world. Hitt, Ireland and Hoskisson [64] examined the Honda Motor

Company and reported that by Honda Motors reduced its production costs by 30% by adopting

flexible production systems through small car and small volume operations. A research on BMW

and Mercedes-Benz cars [65] revealed that they have edge in superior engineering, elevated stature

and excellent quality. Studies have been carried out on the effects of task rotation and working

methods on enhancement of soft issues such as motivation and job satisfaction in automotive

setups in Malaysia [66]. A research on Lexus, a division of Toyota Motor Corporation Ltd has

been conducted by Markides [67] identifying the need of integration in the value chain. Hill and

Hones [68] elaborated upon several different strategies adopted by automobile manufacturers for

customer satisfaction. Authors gave examples of GM’s midsize Cadillac, and Ford’s midsized

products. Authors have highlighted that Toyota, Ford, Daimler-Chrysler, and Mercedes Benz have

employed strategies like integrated cost leadership and differentiation to attain competitive

advantage.

2.5 Role of Government and Productivity Issues in Developing Countries

Zutshi and Gibbons [69] discussed that there has been an active role played by the

governments in Southeast Asia to promote industrial growth both in manufacturing and service


23

fields, which is contradictory to western theories. The authors argued that government

participation, polices and decisions have been the backbone for industrial growth and achieving

competitiveness in this region. This research reviewed two government linked companies (GLCs)

in Singapore outlining their internationalization process from a contextual perspective. Mahadevan

[13] explained two different views on government involvement with a special focus on the role of

the public sector in services and manufacturing: firstly, “Washington consensus” deliberating that

excessive and unfair competition from public sector results in cutting down progress of the private

sector, and secondly, “Developmental state view” debating that there is a dire need for government

to intervene and public sector to actively participate towards economic growth in developing

countries. The author gave the examples of Korea and Singapore emphasizing that in Asia an

active role of the public sector is a must to achieve desired developments. Dependence on public

sector industry specifically the defense industry is a must for under developing countries due to

political and strategic factors [70]. The author expressed that the arms embargo on these countries

has been another major factor for development and expansion of public sector. The research

evaluates establishment of defense industry in Jordan while also examining the same in Brazil,

South Africa, South Korea and Taiwan, pointing out the positive effects they had on the economies

of their countries. Strong effects of Government Policies on productivity of industrial sector has

been studied [4] and it has been recognized that effective and favorable government policies are

essential for productivity enhancement.

2.6 Reasons for Selecting Pakistan and Gap in Literature Review

Pakistan is one of the developing countries with remarkable potentials for manufacturing

enhancement. The automotive industry of Pakistan has shown some improvements mainly due to

enhanced capital inputs but its contribution in GDP and employment is still of modest size.

Particularly, a remarkable difference can be observed compared with other Asian countries like


24

Japan, Korea, Malaysia, India, China and Thailand. In these countries the automotive industry has

exploited the catalytic role in promoting growth of broad based manufacturing sector (Asian

Development Bank Report). One reason for the difference is the fact that very less research has

been carried out on the operational procedures and productivity enhancement possibilities of

Pakistan automotive industry.

Sarwar et al. [71] indicated that Pakistan loses more than Rs. 450 billion annually due to

poor quality, low productivity and wastages. It was also explained that frequently changing

government policies in Pakistan has resulted in slow economic growth. In the beginning, private

sector was relied on for manufacturing and services but in early 70’s policies shifted towards

nationalization. In the late 80’s and 90’s, it was realized that public sector organizations were not

performing as per desired expectations. Hence, declining private sector was given relief through

inclined polices [19]. The Privatization Act 2000 was the first milestone achieved that gave a

remarkable boost to the private industry (Asian Development Bank Report 2008). This act gave

private sector a big boost and Pakistan’s output got a rise to 13 percent in 2005-06 from 5.67

percent in 1959-60 [72]. Federal Bureau of Statistics, Pakistan [73] conducted a survey and it was

found out that the manufacturing industry of Pakistan contributes 19% in the GDP. According to

a survey conducted by them in 2010, it has been stated that the manufacturing industry contributed

18.5% in GDP. This percentage is still quite low as compared to the neighboring countries like

India, China and Malaysia. In order to improve productivity, attention has to be paid to fast

changing world and improve capacity of organizations for change adjustment. It is necessary to

recognize the importance of all major factors, which contribute to or put barriers against

productivity growth. This research has been carried out to measure and evaluate the productivity of

the leading automotive manufacturing companies of Pakistan; while highlighting the flaws in the


25

existing systems and conducting surveys to propose a productivity enhancement framework. In this

research, gap in the body of knowledge regarding the productivity enhancement model for

automotive industry in Pakistan has been researched. After identifying the blemishes and

drawbacks in the prevailing system, a comprehensive productivity enhancement framework has

been proposed. This framework was then validated as a model, in one of the major auto parts

manufacturing factories of Pakistan.

2.7 Contextualization of Research

Development processes and economic growth scenario in developing countries is

drastically different from that of the developed world [1]. The results and solutions of research

conducted in the developed world cannot be implemented in the developing countries without

change, because cultural as well as other differences also play an important role and can give

different results for similar kind of research [74]–[77]. Considering these facts as revealed from

previous research, this research is carried out in one of the major countries of developing world

i.e. Pakistan. This research focuses on the automotive industry and specifically productivity

measurement and productivity enhancement in Pakistan which is a grey area in the Body of

Knowledge (Bok), since research in this specific area is very scanty. Figure 2.2 depicts the

contextualization of this research and the area to be focused in this research. Pakistan automotive

industry has been researched upon with emphasis on productivity measurement and enhancement

possibilities.

Figure 2.2 Contextualization of Research


26

2.8 Factors Affecting Productivity

There has been a consensus amongst the researchers that major factors influencing the

overall productivity of an industrial organization are identified as technology, equipment,

management, personnel, job satisfaction, rules and procedures [5], [6], [17], [78].

2.8.1 Role of Technology

Role of technology has been considered as one of the most crucial factors affecting

productivity of an organization [5], [6], [17], [78]. As per Webster dictionary the word technology

is formed of two Greek words techno meaning “art, skill or craft” and –logía meaning “the study

of something or the branch of knowledge of a discipline”.

Technology is mostly thought of as being consisting of the latest gadgetry, computers and

most modern machines however, [4] indicated this misconception about technology and elaborated

that technology is defined as “any means to accomplish an objective or task”. Sumanth discussed

that there are four types of technologies, product technology, process technology, information

technology and managerial technology. According to the author, process technology is the most

crucial factor for productivity enhancement in any organization. However, in this research all four

types will be considered for productivity enhancement because role of the other three types in

productivity enhancement cannot be ruled out.

Most research is conducted only on the impact of process technologies on performance and

productivity of the enterprises. Several surveys have been conducted on benefits of advanced

manufacturing technologies (AMT) which basically encompasses only the process technologies

[28], [79]–[82]. Thomas et al. [28] conducted a survey on 300 SME’s in UK to investigate the state

of AMT in manufacturing organizations. The survey results were then used to propose a strategic

model for AMT implementation. This research used the most effective methodology used for these

kinds of surveys, a mix of qualitative and quantitative questionnaires. A survey was conducted of

http://en.wiktionary.org/wiki/logia


27

Turkish manufacturing industries and highlighted the effects of overall technical changes on

industrial growth [83]. They argued that technical enhancement is the key towards effective

utilization of resources and productivity enhancement. A detailed evaluation of Korean

manufacturing industries was carried out [84]. The researcher identified and estimated the sources

of technical inefficiency in these organizations.

Coronado [85] conducted a research on impact of information systems (IS) on

manufacturing agility in SMEs. The author used a similar type of survey using qualitative and

quantitative surveys to investigate the issue and as an outcome proposed a framework for

enhancing the manufacturing agility. It was reported in the research that how IS can be used for

enhancing the performance of an organization. In productivity improvement efforts, information

technology has always been considered to be one of the most important aspects. However, debate

and discussion on the role of IT gave rise to the concept of “Productivity Paradox”. Also known

as “Solow Computer Paradox” once Solow [86] pointed out that “You can see the computer age

everywhere but in the productivity statistics”. Brynjolfsson [87] noted the disagreement of

advancement in computer technologies and relatively slow growth of productivity at firm,

individual and national levels. Several other research works have also pointed out this aspect and

emphasized that not all latest technologies are good for all kinds of scenarios. It is duty of the

management to decide how much and where to invest in IT [4], [44]. This aspect also holds true

for other kinds of technologies as well.

McTavish et al., [44] established a framework for improving productivity. They talked

about a new trend for productivity improvement i.e. concentrating on “knowledge workers” to

enhance productivity. The authors emphasized that despite the fact that a number of new

technologies, concepts and techniques have been proposed and developed but still there is a need


28

to make a choice between them in different scenarios in order to enhance productivity. They talked

about Zero Inventory (ZI), Just in Time (JIT), Flexible Manufacturing System (FMS), Optimized

Production Technology (OPT), Computer Integrated Manufacturing (CIM), Activity Based

Costing (ABC), Quality Function Development (QFD) and Total Quality Management (TQM).

They gave a generalized solution to make different combinations of these technologies in order to

increase output and also proposed a strategic framework to enhance productivity. However, this

framework was so generalized that there is still a need to propose and establish frameworks for

different industries.

The effectiveness of different management technologies have also been researched upon.

Saad and Patel [38] investigated the possibilities of Supply Chain Management (SCM) for

performance measurement in the Indian automotive sector. Authors indicated that there are very

few attempts to research the aspects and practices of SCM in developing countries and especially

in India. The findings of the research gave alarming results that the world’s best technologies like

SCM and balance scorecards may not be very effective to use in India until and unless proper

grounds are prepared for the purpose. This research further augmented the belief that there is a dire

need to conduct a study in Pakistan automotive industry as well.

Park [16] coupled productivity with the Six Sigma concept and explained as to how Six

Sigma implementation has improved the productivity of several firms in Asia. Productivity and

quality relationship has also been clarified to be interdependent and that none is useful without

augmentation and emphasis of the other. On the other hand different results have been shown in a

research conducted in Brazil [63]. They worked on benchmarking the Six Sigma application in

Brazil and found out that organizations fail to implement the Six Sigma concepts successfully

without fulfilling the basic criteria. They highlighted that lack of managing ability is one of the


29

major causes of several failures of Six Sigma implementation. Secondly, a specific number of

black belts, green belts must be trained first within the organization before trying to implement

this concept.

A research was carried out in Finland on managerial perceptions of productivity in public

sector [25]. They conducted a survey and reported that there is a misconception about productivity

in this sector. It was also reported in the research that some respondents were not able to define

productivity at all, indicating that there is a dire need in the industry to work on this aspect to

enhance performance and profits. Grünberg [22] carried out a detailed historical review of

improvement methods in manufacturing operations. The author reviewed the latest techniques and

methods from 1776 to 2003. Author discussed methodologies adopted in Japan and USA including

Total Preventive Maintenance (TPM), 5S, Kaizen, Benchmarking, Toyota Production System

(TPS), Theory of Constraints (TOC), Business Process Reengineering (BPR), Lean Manufacturing

and Deming’s Wheel of improvement. He also linked these with improvement of profits,

performance and productivity. It was also pointed out that most of the techniques once used in

western settings proved unsuccessful due to cultural differences. The limitations of these

techniques and methods were also pointed out in this research while proposing measurement model

and performance factor model to fill the gap. An important finding of the review was that only

after measurement one can decide which tool to use for performance enhancement. Another aspect

pointed out by this research was the fact that all these techniques are too general as they come

from different fields. Hence, there is always a need to specify which technologies are most

effective for different industries.

The list of productivity enhancing tools used by different industries has been enumerated

by Performance Management, Measurement and Information (PMMI) report [88]. A detailed


30

review of mostly used technologies and techniques was carried out and a list of 15 most used

techniques has been elaborated upon in this report. This report is an excellent review of the

technologies used, but it only concentrates on performance as an outcome. Harrington [43]

proposed a new model with the concept of total improvement management. Author pointed out

that most of the research and management decisions focused on quality issues and aspects with the

view that improvement will be achieved on successful implementation of quality solutions only.

In a detailed literature review, the author discussed the contribution of quality Gurus while

highlighting that no single methodology gives a perfect solution and highlighted the confusion of

management as to which technology should be chosen. It was elaborated that mostly all

management technologies require a major portion of resources. Furthermore, the effect of

frequently changing decisions of management on the performance of an organization was also very

effectively highlighted. This research again focused on a need to develop customized solutions for

different industries.

On the basis of this extensive literature review, the author felt that a productivity

enhancement framework specifically for the automotive manufacturing industry of Pakistan

should be developed, which can also be generally used in other developing countries with some

minor modifications. A similar concept was used by Davis [89] as he proposed Technology

Acceptance Model (TAM). This model is probably the most accepted and cited model, though it

was basically proposed for computer usage and information technology only. The authors also

gave the concepts of perceived usefulness (PU) and perceived ease of use (PEOU). PEOU is

defined in this research as “the degree to which an individual believes that using a particular system

would be free of physical and mental effort”, and PU as “the degree to which an individual believes

that using a particular system would enhance his/her job performance”. Davis emphasized that


31

“user acceptance is often the pivotal factor determining the success or failure of an information”

[90]. As an extension of TAM, TAM2 was proposed [91]. In this new extension, the authors

included social influence process and cognitive instrumental process. There is a dire need that a

similar kind of TAM should be developed for other aspects of technology i.e. process technologies,

product technologies and managerial technologies.

Knowledge management is a field which has caught the notice of researchers and academia

all over the world. Sigala and Chalkiti [92] linked the concept of knowledge management with

performance improvement. The importance of knowledge management for any kind of

improvement in any field was highlighted by the authors. The authors elaborated that there are

different definitions of Knowledge but they defined it as “actionable information”. In an extensive

literature review conducted in this research, the two dimensions of knowledge advocated upon

have also been explained which are Explicit Knowledge (EK) and Tacit Knowledge (TK). TK is

defined as “type of knowledge that cannot be expressed and transcribed in written form, as it is in

our minds only” whereas EK is defined as “knowledge that can be transmitted into formal

language”. As per the point of view of the author EK is just a tip of the iceberg and world of

knowledge lies in the invisible part that is TK which has to be explored. The importance of TK for

enhancing business performance has been discussed and studied in this research. It was also

indicated that different performance (and productivity) improvement techniques like supply chain

have been investigated in the light of knowledge management in the past, however specific studies

focusing on TK are not traceable. The problem for externalization and ultimately utilization of TK

has been elaborated in this research conducted on Greek Hotels. The important finding of the

survey of this research is very relevant and important for my research because a lot can be explored


32

and utilized for productivity enhancement from the extension and utilization of TK in Pakistan

automotive industry. So TK has been added as an important variable in this research.

2.8.2 Impact of Job Satisfaction

During the past few decades, job satisfaction of the employees in both public and private

sectors has received intensive research. The scholarly attention on job satisfaction is not surprising

because it is a strong predictor of productivity [93], [94] and job performance, which ultimately

lead to high employee retention [95]. Job Satisfaction has also been found to be negatively related

to turnover [96] and absenteeism [97]. Organizations need to promote job satisfaction in their

employees in order to prevent job withdrawal and boost productive performance. Interestingly,

literature has recognized differences in levels of satisfaction across cultures [74]. Job satisfaction

due to intrinsic motivational factors is found to be higher in individualistic countries; whereas,

extrinsic factors provoke higher satisfaction level in collectivistic cultures [98]. A positive

relationship between collectivism and job satisfaction is also found in one of the studies [99].

Another study found that job satisfaction is higher in the U.S. than in Japan [74]. The cultural

differences also have to be taken into account while interpreting the findings of this research

because the results of the western world do not necessarily hold true for the eastern world (and

vice versa) as indicated by previous studies conducted in non-western work settings [74]–[77]

Job Satisfaction is the sense of achievement, accomplishment and pride felt by employees

in their respective job settings and is believed to be ‘‘an attitude toward one’s job’’ [100]. There

are many factors which influence job satisfaction and its importance was earlier realized by

Herzberg et al. [101]**. Later, Herzberg’s theory was tested for its validity in different work

** In motivation-hygiene theory, he identified six factors achievement, recognition, work itself, responsibility,

advancement and growth, which cause satisfaction and named them “Motivators”. Another six factors identified were

company policy, supervision, relationship with boss, work conditions, salary and relationship with peers which might

cause dissatisfaction and were called as “Hygiene factors”.


33

settings by many researchers. The study on Thai construction engineers and foremen [102] showed

that motivators contribute to job satisfaction, while hygiene factors lead to dissatisfaction. The

quest of increase in job performance compelled administrators to identify factors that foster

employees’ work satisfaction. A comparative analysis [103] was conducted between the public

and private sector employees of Florida U.S.A. The results revealed that the public sector value

the extrinsic factors significantly higher than those in the private sector. Private Sector employees

were found to be more inclined towards intrinsic factors [104]. However, significant empirical

studies carrying out analysis of satisfaction level of public sector organizations in South East Asian

countries are rarely found. A qualitative study was conducted to investigate the important factors

necessary to increase the level of job satisfaction in the public service sector of Pakistan [105].

The extent of research exploring the effects of job satisfaction on productivity is limited in both

private and public sectors of Pakistan, and very rare in the automotive manufacturing industry.

Hence there is a dire need to further explore this relationship.

Chapter Summary

The expansion of international trade, globalization of economies and emergence of new

markets have made productivity a critical success factor for any country in the world. A lot of

research has been conducted in the world on productivity due to this aspect. Several productivity

improvement models have been suggested in the past. One of the major issue with these models

was that performance was considered as the desired outcome instead of entirely focusing on

productivity. Tangen [27] gave the PPP model differentiating these terms. Due to this addition in

BoK, researchers all over the world started developing productivity enhancement models for their

industries. Pakistan is one of the developing countries with remarkable potentials of manufacturing

enhancement. The automotive industry of Pakistan has shown some improvements mainly due to

enhanced capital inputs, but its contribution in GDP and employment is still of modest size. There


34

is a dire need to work on productivity enhancement of this industry so that it can play a vital role

in GDP of the country. In this chapter a detailed literature review has been conducted which has

identified that development of customized productivity enhancement model for Pakistan

automotive industry is essential. Several different methodologies used all over the world for

productivity enhancement e.g. role of technology, have also been discussed in detail.

Chapter 3- Research Methodology

35

CHAPTER 3

RESEARCH METHODOLOGY

3.1 Preface

Several productivity enhancement models have been proposed in the past but measurement

in that specific area is a must for any kind of enhancement [4]. Proposing a productivity

enhancement model without measuring and depicting the prevailing status is useless. Sumanth [4]

proposed Total Productivity Management (TPgmt) in which measuring productivity is the first

stage, evaluating productivity is the second, productivity planning is the third and productivity

enhancement activities is the fourth stage. This model was followed in this research and first the

prevailing productivity status was measured quantitatively from secondary data. Based on these

results qualitative research was done to find the knowledge about productivity in this industry.

Thereafter, the prevailing productivity enhancement best practices used in the industry were found.

These best practices were compared with the best practices followed in the world and a

comprehensive productivity enhancement model was proposed based on this comparison. The

proposed framework was implemented in one of the major auto manufacturing companies of

Pakistan. The results were monitored after implementation to confirm the validity of the model.

Detailed description of the procedures followed and samples selected are given in the succeeding

paragraphs.

This mix methods research was conducted using sequential explanatory design in

combination with sequential exploratory design as suggested by Creswell* [106]. Firstly,

quantitative research was conducted in order to measure the prevailing productivity status of the

* John W Creswell is considered to be one of the best experts in mix methods research. He is Author of several

books on mix methods research and founder of the first mix methods journal, International Journal of Mix Methods

Research. In his book “Research Design: Qualitative, Quantitative and Mix Methods Approaches” (2013), he gave

six research designs for mix methods research, Chapter 10.


36

industry. A detailed productivity analysis of two major automotive manufacturing companies for

10 years span i.e. 2000 to 2010 was conducted. This analysis gave the status of the prevailing

productivity. Further, in order to find out the productivity knowledge and the best practices

followed in the industry, qualitative research was done. Interviews of 40 CEO’s and top managers

were completed from 26 companies of automotive industry all across Pakistan. This qualitative

research was conducted to develop a comprehensive productivity enhancement framework. The

results hence obtained were implemented in a functional factory at Lahore. In order to check the

validity of the model, another quantitative research was done on the secondary data in order to

check the validity of the model. This combination of first conducting quantitative research and

then, on the basis of its results, conducting qualitative research is known as Sequential explanatory

design†. In the second stage of the research, results of qualitative data analysis were used to

conduct quantitative analysis; this model has been named as Sequential exploratory design by

Creswell [106].

The main theme of this research was to enhance the productivity of these organizations.

This dependent variable of productivity enhancement is affected by several independent variables.

This research was conducted to find out the most important and promising variables which cause

some increase in the productivity of these organizations. These variables were identified with the

help of qualitative research conducted and their importance was confirmed with the help of the

results of implementation of these on ground in actual industrial settings.

† Sequential Explanatory Design was proposed by Creswell in his book Research Design: Qualitative, Quantitative

and Mix Methods Approaches (2007) page 209. In this type of research first quantitative research is conducted and

on the basis of the results qualitative research is conducted. Results of both are compiled for finalization of results.


37

3.2 Research Process

This research was conducted in four stages:-

Stage I Productivity Status of the industry was measured using quantitative

methodology.

Stage II Based on the results of first stage qualitative methodology was used,

in order to analyze knowledge of the industry about productivity and to develop a

comprehensive productivity enhancement framework for the industry.

Stage III Based on the results of the second stage the proposed framework

was implemented in one of the major auto manufacturing industry.

Stage IV Quantitative methodology was used to measure and compare

production increase, revenue generations and inputs used before and after the

implementation of the model to prove the validity of the model.

3.2.1 Stage I Productivity Measurement using Quantitative Methodology

Automotive manufacturing industry of Pakistan prospered during 1980’s and 1990’s owing

to inflow of foreign direct investment (FDI). During this period, world renowned automotive

manufacturing companies like Honda, Toyota and Suzuki launched their manufacturing plants in

the country. This industry flourished further after 2000 due to favorable polices adopted by

Government of Pakistan. Presently there are more than 21 automotive manufacturing companies

in Pakistan, out of which only three are car manufacturers, including Honda Atlas, Indus Motors

and Pak Suzuki. This study has focused on two wheelers as well as four wheelers, automotive

assemblers and auto parts manufacturers.


38

3.2.1.1 Data Sampling and Under Study Organizations

For productivity analysis, two major market share holding companies were selected out of

three cars- manufacturing companies in Pakistan. The two companies selected were Indus Motors

(principle is Toyota Motors) and Honda Atlas (principle is Honda Motors). The major reason for

selecting these companies was that only these two companies compete in nearly same nature of

cars i.e. 1300cc to 1800 cc cars. A detailed productivity analysis of these companies was carried

out over a span of 10 years’ time i.e. from the year 2000 to 2010. In order to measure productivity,

the most important aspect is to collect reliable, valid and detailed data including all aspects. It was

indented to measure Total Productivity as proposed by Sumanth [4], as well as all partial

productivities and Total Factor Productivity (TFP) using Cobb-Douglas function.

3.2.1.2 Data Collection

Data of the employees, their wages, total man-hours consumed, fixed capital input,

working capital input, cost of materials used, cost of energy utilized, cost of all other expenses;

including taxes, traveling expenses, and all other overheads was required. Furthermore, outputs,

in terms of both quantity and value were also required. All these details required secondary data

of the organizations. Asking companies about their capital investment including fixed and working

capital, employment details including wage rates, materials cost, energy expenses and other

overheads is a sensitive issue and inquiries like these can sometimes offended people, especially

in a country like Pakistan where such kind of research culture is still in nascent stage. Similar

problems were faced during data collection for this research directly from the companies. Owing

to failure to directly collect complete data from companies despite best efforts, the following

process was resorted to:


39

Firstly, internet search was conducted and two associations who maintain the detailed data

of Pakistan automotive industry, namely Pakistan Automotive Manufacturers Association

(PAMA) and Pakistan Association of Automotive Parts and Accessories Manufacturers of

Pakistan (PAAPAM) were consulted. A lot of information and data was gathered from these

associations. However, in certain aspects the data were incomplete for comprehensive productivity

measurements. Therefore, as an alternative for data collection, certain government organizations

like Ministry of Industries and Production of Pakistan (MOIP), Engineering Development Board

of Pakistan (EDB), Securities and Exchange Commission of Pakistan (SECP) and Federal Bureau

of Statistics Pakistan were consulted, because all organizations submit their organizational details

to these government agencies. Thus some important information was retrieved by using these

sources. A major problem with the data was that data gathered from these organizations was not

compiled keeping in view measurement of productivity, rather it was more inclined towards

financial issues only. During this process, it was felt that productivity awareness in Pakistan

industry needs more up gradation. The third option available was financial reports of these

companies. Therefore, the most reliable and valid sources of data of any company; i.e. their audit

reports were selected. The data extracted from these reports filled a huge gap in compiling the

productivity analysis of automotive industry. However, two key drawbacks of this data were that

available data on these reports had been prepared and compiled with a view to present the financial

status of the companies and not for measuring productivity. Secondly, in these reports sales’ of

products are the main aspect of emphasis whereas data of quantity produced are required for

productivity analysis. In order to retrieve required data from productivity point of view, several

formulae were derived. Details of these derived formulae are reported in Annex ‘A’. Output value


40

of the products was taken from the firms and ex-factory prices were considered. The book value

of property, plant and equipment were taken for fixed capital.

3.2.1.3 Data Analysis

In order to understand the productivity status of these automotive manufacturing firms, the

overall production status of complete automotive manufacturing industry of Pakistan was analyzed

over a span of 5 years i.e. 2005 to 2010. Then productivity analyses were carried out for both the

firms under study. The detailed data of these companies were compiled into XL sheets. GDP

deflator was used in order to deflate all the values in terms of the base year i.e. 2000. The problem

with using consumer price index (CPI) is that it requires details of all materials and other inputs

used which were not available. Since only the monetary values of these inputs are available,

therefore GDP deflator was used. Double deflation was carried out for computing value added

output. Partial productivity measurement tools as suggested by previous research [4], [10] were

applied to measure the productivity status of these automotive manufacturing companies of

Pakistan.

Partial Productivity of One Class of Input = Gross Output

Input Value of one class of input (1)

Separate columns were constructed for all partial productivity measures i.e. labor productivity,

material productivity and capital productivity. Formulae of these measures were entered into these

columns for easy calculations. Different graphs were plotted for graphical representation of the

analyses.

For calculating Total Productivity of these firms, the formula as suggested by [4] was

utilized.

Total Productivity = 𝐺𝑟𝑜𝑠𝑠 𝑂𝑢𝑡𝑝𝑢𝑡

𝐼L + 𝐼 M + 𝐼 F,C+ 𝐼 W,C + 𝐼 E + 𝐼X (2)


41

However only the Operational Total Productivity were calculated in which

Output = value of Finished units produced + value of Partial units produced

For the purpose of all further references in the paper, Total productivity will be meaning

operational total productivity. IL is labor input wages in value terms, IF.C is fix capital input, IW.C

is working capital input, IM is materials input in value terms, IE is energy consumed and IX is all

other expenses of the firm including taxes, travelling charges and all other overheads. Total

Productivity (only operational total productivity) of the firms was calculated and productivity

indices for ten years were computed.

TFP was calculated using Cobb-Douglas production function.

Q = ALαKβ (3)

Where Q is gross output in value terms, K is fixed capital, L is labor man-hours utilized (another

variance using number of employees was used), α and β are elasticity’s respectively for L and K

and A is role of technology.

Another variance of this function was also utilized

Y = ALαKβ (4)

Where Y is value added output i.e. gross output minus the intermediate goods and services utilized.

Rest all variables remaining similar.

These equations were transformed into the log equation so that regression would be run on

them. So the equation 3 and 4 become

Ln (Q) = Ln. A + α Ln. L + β Ln. K (5)

Ln (Y) = Ln. A + α Ln. L + β Ln. K (6)


42

Simple and multiple regressions were run on these equations in order to determine the

elasticity’s of both labor (L) and capital (K). As A is role of Technology so value of Ln. A was

transformed into numeric term by using exponential factor Ln A = -x = e-x = z

3.2.2 Stage II Developing Productivity Enhancement Model using Qualitative Research

3.2.2.1 Sampling Techniques and Understudy Participants

A mix of both face to face interviews and telephonic interviews were conducted from

CEO’s, Managing Directors, directors and general managers of automotive enterprises. These

enterprises included Pak Suzuki, Indus Motors, Honda Atlas, Millat Tractors, MEL, Al-Ghazi

Tractors, Ravi Autos, Super Asia, Infinity Engineering, Pakistan Springs and Engineering

Company, Master Motors and several other companies. Interviews conducted ranged from 15 to

30 minutes. Most of the respondents agreed to the interview on the condition of anonymity.

Already made question guide as given at annexure B was used. However, as per wish and will of

the respondents sequence of questions was changed for their ease and comfort. Theoretical

sampling was done on the basis of theoretical saturation phenomenon as suggested by Byman and

Bell [107], and a sample size of 40 was completed from 26 companies of automotive industry.

Multistage sampling was conducted making a combination of cluster sampling, stratified sampling,

random sampling and, on several occasions, snow ball sampling techniques. These combinations

were used in order to achieve maximum randomization and to avoid biased sampling.


43

3.2.2.2 Data Collection

Grounded theory strategy‡ was used for data collection and analyses, as suggested by

Strauss and Corbin [108]. For productivity survey of the industry, interviews§ were conducted

using open ended questions as per the precedence from the world recognized research carried out

in the past [4], [25], [28], [38], [92]. Considering the requirement of this research semi structured

interviews were conducted because similar research methodology has been used in the past in

different countries to solve similar kind of problems [4], [25], [28], [38], [63], [85], [92]. This

action research was done utilizing ethno methodology. Ethnography and participant observation

in combination with qualitative interviewing was conducted as suggested by Bryman and Bell

[107]. Triangulation methodology, as conceptualized by Webb et al. [109] was utilized to avoid

going native, as the researcher was performing as General Manager Productions in an organization

of the same industry which is the target population of this research. To ensure external reliability,

semi structured qualitative interviewing was conducted using an interview guide consisting of 11

items extracted from the published work, attached as Annex ‘B’ [4], [25], [28], [38], [92]. Results

obtained and concurrence of the researcher’s ideas confirmed the internal reliability and internal

validity of the research. External validity was limited only for similar type of organizations.

3.2.2.3 Data Analysis

Computer Aided Qualitative Data Analysis (CAQDAS)** were used for data analyses. Data

compiled in field notes and responses of the respondents were transcribed verbatim, entered into

‡ Grounded Theory is a qualitative research technique which was described and elaborated by Glaser and Strauss

(1967). There has been some criticism of this technique by some authors (Charmaz, 2003; Bringer, Johnston and

Brackenridge 2004) due to some quality issues but due to its diversity this technique has gained popularity and has

been the most extensively used qualitative analysis technique in the recent past (Hood 2007). § The importance of interviews to carry out a research has been deliberated upon a lot in past (Muchinsky, 2003; Davis

2004). Davis (2004) in his research carried out an extensive literature review of this aspect and pointed out the

differences of several authors about structured, semi structured and unstructured interviews. ** CAQDAS is perceived and accepted by experts as it can greatly enhance the data handling and data analysis

procedure (Bringer, Johnston, and Brackenridge, 2006a, 2006b; Bringer et al., 2004).


44

XL and then imported into NVIVO version10. Several audio and video proofs were also gathered

and entered because NVivo has the capability to handle and help in analyses of these kind of data.

Grounded theory strategy was use for data analyses as suggested by Corbin and Strauss [108].

Themes that emerged from the data were coded using tree nodes. Coding sequence of open coding,

axial coding and selective coding as suggested by Corbin and Strauss [108] was also done. On the

basis of constant comparison concepts and categories were extracted from the data. Ethnographic

content analysis (ECA) as suggested by Altheide [110] was conducted which resulted in

formulation of substantive theory. Formal theory could not be explored from this substantive

theory as the research was conducted in similar organizations. However, alternate methodology

was utilized for generation of formal theory; by comparing this substantive theory with existing

theory and comparable settings, as suggested by Bryman and Bell [107].

3.2.3 Stage III Implementation of the Proposed Framework

Developed framework was implemented in one of the major company of automotive

industry. The researcher was performing as GM Productions in one of the biggest Auto Parts

manufacturing plants in Pakistan. The status and position ensured that these management

techniques and manufacturing technologies were implemented in true letter and spirit. The

implementation of the framework required a complete cultural change; hence stage wise

implementation was adopted. This stage wise implementation ensured a gradual shift towards the

betterment and productivity enhancement. Detailed implementation methodology is explained in

chapter 7.

3.2.4 Stage IV- Validation of model by Quantitative Analysis

After implementation of the techniques as proposed in the framework, complete analysis

of the firm’s record was conducted. In this analysis the financial effects of the revenue difference


45

of year 2010, 2011 and 2012 was done. Production in numbers, reduction in manpower, reduction

in other inputs like electricity and material were also calculated. The detailed methodology and

results of this analysis are explained in chapter 8. Especially elaborated points of this report include

the results of energy audits, production graphs, human resource saving, development projects

successfully completed, KAIZEN’s achieved and revenue generation.

3.3 Reliability and Validity

3.3.1 Reliability

The reliability of the qualitative data was tested as per methodology given by Bryman and

Bell [107]. There are two types of reliability to be tested: internal reliability and external reliability.

As per Bryman and Bell [107] external reliability is the extent and degree to which a study or

research can be replicated and internal reliability is the matching of the ideas of research. To

ensure external reliability semi structured qualitative interviewing was conducted using an

interview guide consisting of 11 items extracted from the published work, attached as Annex ‘B’

[4], [25], [28], [38], [92]. Results obtained and concurrence of researcher’s ideas confirmed the

internal reliability of the study.

3.3.2 Validity

Validity also has to be tested for both external validity and internal validity [107]. For this

research, the convergence of the ideas conceived by the researcher in the start of research and the

end results of the study proved the internal validity of the research. For external validity, same

research has to be conducted in similar kind of organizational settings which was not done in this

study. Alternative methodology was used to prove the external validity and to generate the formal

theory; i.e. by comparing the substantive theory of this research with existing theory and

comparable settings, as suggested by Bryman and Bell [107]. For this, the results of this study


46

were compared with the productivity enhancement model of USA, UK, India, China, Sweden and

Thailand [33], [36], [37], [44], [45]. On the basis of this comparison finalized model was proposed.

Chapter Summary

Research methodology utilized for conduct of this research work has been elaborated in

this chapter. Due to the complexity of the issue in hand mix methods research was conducted.

Sequential explanatory design in combination with sequential exploratory design as suggested by

Creswell [106] has been used. In the first stage quantitative research was conducted in order to

measure the prevailing productivity status of the industry. Further, in order to find out the

productivity knowledge and the best practices followed in the industry, qualitative research was

done in the second stage. Interviews of 40 CEO’s of automotive manufacturing plants were

conducted and the responses were analyzed with NVIVO software. This qualitative research was

conducted to develop a comprehensive productivity enhancement framework. The results hence

obtained in the form of productivity enhancement framework, were implemented in a functional

organization in order to check the validity of the model in the third stage. Results of these

implementations were checked with the help of another quantitative research on the outcomes in

the fourth stage. This combination of first conducting quantitative research and then, on the basis

of its results, conducting qualitative research is known as Sequential explanatory design. In the

second stage of the research results of qualitative data analysis were used to conduct quantitative

analysis; this model is known as Sequential exploratory design.

Chapter 4- Results of Quantitative Analysis

47

CHAPTER 4

RESULTS OF QUANTITATIVE ANALYSIS: MEASURING

PRODUCTIVITY

4.1 Profit and Loss Statements Analysis

Trend line of the industry was an important factor in analyzing the productivity status of the

two automotive manufacturing firms under study. In order to understand their business status,

detailed analyses of these firms were done on their secondary data; i.e. financial statements. Firstly,

profit and loss statements of these firms were analyzed. Figure 4.1 shows the profit and loss (PLS)

status of both Indus Motors and Honda Atlas from FY 2000-2010. It shows that both firms were

at approximately similar profit levels in the base year 2000-2001. In FY 2001-2002 Honda Atlas

took the lead. But in FY 2002-2003 Indus Motors enhanced its profits by four times and since then

it continued to increase its profits. The profits declined only in FY 2007-2008 and FY 2008-2009

but it parallels the overall situation for the Industry (as per their financial statements). The poor

performance in these two years can be attributed to the overall political and economic instability

in the country. Indus Motors however, showed remarkable profits in FY 2009-2010. Honda Atlas

on the other hand could never catch up with Indus Motors since FY 2002-2003; rather it showed

reduced profits in 2004-2005 and a huge loss in FY 2006-2007. In FY 2007-2008 it recovered

from loss but again in 2008-2009, it showed a loss and especially in FY 2009-2010 it showed a

loss of 8.522 billion rupees – the biggest loss by any automotive manufacturing company in

Pakistan. The trend shown by Honda was totally different from the rest of the industry and

warranted further investigation and probing in order to identify the reasons for this phenomenon.


48

Figure 4.1 Profit and Loss Status of Indus Motors and Honda Atlas (Financial

Statement)

4.2 Production Capacity Vs Productions Output Analysis

Figure 4.2 shows the trend line for total production volume depicting a similar picture as has

been elaborated in the Profit and Loss graph. To further augment the findings, capacity verses

output graphs of both firms were plotted as shown in Figure 4.3. These graphs depict that Indus

Motors had been producing nearly at the optimum level of capacity since FY 2002-2003 except

for FY 2008-2009, which is in line with the trend of the industry. Honda Atlas on the other hand

was producing more than its capacity till FY 2005-2006. Honda shows its capacity on a single-

shift basis whereas Indus shows capacity on a double-shift basis. Again, these graphs showed that

something drastically went wrong in FY 2006-2007 and since then the performance of Honda Atlas

has been deteriorating. Another interesting point is that in FY 2006-2007 the production levels of

the company kept on decreasing but the capacity level was enhanced to a maximum level of 50,000

units. It is not understandable as to why capacity been enhanced for a manufacturing plant which

is going in loss and is not able to produce even 50 per cent of the previously available capacity?

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

Honda Profit 204471 431642 346135 408683 162179 705294 -264540 75010 -401833 -852200

Toyota Profit 203370 360463 1257614 1473242 1484646 2648464 2745701 2290845 1385102 2719850

-1500000-1000000

-5000000

50000010000001500000200000025000003000000

Rs.

in (

00

0)

Profit & Loss


49

Figure 4.2 Line Graph Showing Production Trend Line of Indus and Honda

Motors

4.3 Results of Productivity Analysis of the two firms under study

In order to carry out the detailed investigation of the reasons for these puzzling trends,

productivity analyses of both firms were necessary. For this analysis, first the partial productivities

of both firms were computed using equation 1. Figure 4.4a shows labor productivities (as per the

formulae given in Annex A) of both Indus Motors and Honda Atlas over a span of ten years, i.e.

FY 2000-2010. The labor productivity graph for both the firms showed a remarkable resemblance

to the output graphs of the firms, showing presence of a strong correlation between the two. The

labor productivity of Honda Atlas kept on growing, but in FY 2006-2007 it had a big dip identical

to the dips in production outputs and loss. It can be inferred from these graphs that inefficient

utilization of labor caused these slumps in performance of the firm. Material productivities of the

firms are shown in Figure 4.4b.

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

Honda Output 5824 8001 6113 11586 20040 31476 18240 15080 12780 11980

Toyota Output 13942 10305 20486 29222 34928 41552 47821 48222 34298 50557

0

10000

20000

30000

40000

50000

60000

Un

its

Pro

du

ced

Honda & Toyota Production


50

a) Honda Capacity Vs Output Graph

b) Toyota Capacity Vs Output Graph

Figure 4.3 a) and b) Honda and Toyota Capacity verses Output

05000

100001500020000250003000035000400004500050000

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

Honda Output 5824 8001 6113 11586 20040 31476 18240 15080 12780 11980

Honda Capacity 5000 5000 3750 11880 17500 30000 35000 50000 50000 50000

No

of

Un

its

Pro

du

ced

Honda Capacity vs Output

0

10000

20000

30000

40000

50000

60000

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

Toyota Output 13942 10305 20486 29222 34928 41552 47821 48222 34298 50557

Toyota Capacity 26000 26000 26000 30000 37000 44298 53040 53040 53040 53040

No

of

Un

its

Pro

du

ced

Toyota Capacity vs Output


51

This graph depicts that material productivity of both the firms kept on growing with a minor drop.

So it can be inferred that no problem of inefficient utilization of materials prevailed in both the

firms. However, the graph also portrays that Indus Motors had a big jump in FY 2009-2010 in

material productivity, which shows its better and more efficient utilization of materials in this

financial year. This can be a big contributor to the enlarged outputs and profits of Indus Motors in

the same fiscal year. Capital productivity graphs of both firms are shown in Figure 4.4c. This graph

explains the most logical and relevant reason for the poor performance of Honda Atlas since FY

2006-2007 and onwards. Poor capital utilization seen here looks like the prime cause for the drop

in profits and outputs of the firm from this year onwards. The huge capital invested in 2006 should

have given more profits but instead its poor utilization resulted in very low capital productivity.

The huge losses shown by the firm most probably were the result of this aspect which needed to

be explored. Total operational productivities and total productivity indices of the firms were also

computed over a similar span of ten years. Figure 4.5 shows total productivities of Honda Atlas

and Indus Motors (Toyota). Figure 4.6 shows total productivities indices of the firms. Comparison

of the two firms gave similar results as in previous graphs i.e. a sudden drop in productivity of

Honda Atlas from FY 2006-07 and onwards. However, another important aspect to be analyzed

here is that productivity analyses of firms in different countries have shown that automotive firms

grow from low to high productivity levels of even 5 and above over a span of five to six years.

However, in Pakistan even flourishing firms like Indus Motors had shown an increase of

productivity from 0.97 to a maximum of 1.88 over a span of ten years, which is very low as

compared to other developing countries. In order to confirm existence of a relationship between

profits of the firm, output produced, total productivity, partial productivities Person’s product

moment correlations were run in SPSS.


52

a) Comparison of Labor Productivities of Honda and Toyota

b) Comparison of Material Productivities of Honda and Toyota

c) Comparison of Capital Productivities of Honda and Toyota

Figure 4.4 a), b) and c) Comparison of Partial Productivities of Honda and

Toyota

0.0020.0040.0060.0080.00

100.00120.00140.00160.00180.00

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

Honda labor Productivity 61.64 71.22 62.82 81.77 118.45130.93 61.27 66.60 60.82 68.31

Toyota Labor Productivity 72.15 55.36 95.77 121.78125.26120.00132.24118.63 94.88 167.40

Pro

du

ctiv

ity

Honda & Toyota Labor Productivity

0.001.002.003.00

Pro

du

ctiv

ity

Years

Honda & Toyota Material Productivity

Honda Material Productivity

Toyota Material Productivity

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

Honda Capital Productivity 11.95 18.69 14.07 21.29 33.84 16.03 5.49 5.40 4.07 5.52

Toyota Capital Productivity 8.27 7.12 17.02 29.46 32.47 24.76 24.72 13.97 12.46 21.03

0.0010.0020.0030.0040.00

Pro

du

ctiv

ity

Honda & Toyota Capital Productivity


53

Results are presented in Table 4.1. In the first matrix, results are presented for Honda Atlas

whereas in the second matrix results are presented for Indus Motors (Toyota). For Honda Atlas

profits of the firm were moderately correlated (γ = 0.49 to 0.61) to all partial productivities and

total productivity of the firm with statistically significant results (p > 0.05 and p> 0.1). Total

productivity was found to be strongly correlated (γ 0.781; p > 0.01) with capital productivity and

strongly correlated (γ 0.813; p > 0.01) with labor productivity at statistically significant results.

Labor productivity was found to be strongly correlated (γ 0.80; p > 0.01) with output and

moderately correlated (γ 0.5; p > 0.1) with number of employees. Employees’ number was found

to be strongly correlated (γ 0.887; p > 0.01) with output of the firm. For Indus motors, profits of

Figure 4.5 Total Productivities of Honda Atlas and Indus Motors

Figure 4.6 Total Productivities Indices of Honda Atlas and Indus Motors

0.000.501.001.502.00

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

Honda Productivity Index 1.00 1.05 1.05 1.09 1.13 1.14 0.96 1.01 0.91 1.04

Toyota Productivity Index 1.00 0.97 1.08 1.15 1.21 1.25 1.45 1.43 1.25 1.81

Pro

du

ctiv

ity

Ind

ex

Honda Toyota Productivity Index


54

the firm were moderately (γ = 0.549) to strongly (γ =0.8561) correlated with partial productivities

of the firm with statistically significant results (p > 0.01 to p > 0.1). Profits were found to be

strongly correlated (γ 0.80; p > 0.01) with total productivity. Total productivity was found to be

strongly correlated (γ 0.983; p > 0.01) with material productivity and strongly correlated (γ 0.891;

p > 0.01) with labor productivity at statistically significant results. Labor productivity was found

to be strongly correlated (γ 0.879; p > 0.01) with output and strongly correlated (γ 0.744; p > 0.1)

with number of employees. Employees’ number was found to be strongly correlated (γ 0.946; p >

0.01) with output of the firm. Outputs of the firm were found out to be strongly correlated (γ 0.899;

p > 0.01) with total productivity of the firm.

4.4 Measuring Productivity with Cobb-Douglas Production Function

To further investigate the problems of low productivity especially in Honda Atlas, regression

tests were run in SPSS. For regression tests Cobb-Douglas production function duly transformed

in log equations were computed as per equation 5 and 6. Descriptive statistics are presented in

Table 4.2. Results of regression tests in the form of nonstandardized coefficients are shown in

Table 4.3. Non standardized coefficients of the regression tests showed significant values (β = -

7.26036, p < 0.05), for Ln man hours (β = 1.707, p < 0.01) and marginally accepted significant

values for Ln Capital (β = -.137, p < 0.1). The relationship showed a high value of R (0.979) and

high lower variance (R² = .958; p < 0.01). Adjusted R² showed a value of 0.946.

The regression equation of log function and Cobb- Douglas production function for value

added computed for Honda Atlas are

Ln. (Y) = -7.263 -0.137 Ln. (K) + 1.707 Ln. (L)

A = e.-7.263 = 0.0007

TFP(Y) = 0.0007L1.71K-0.13


55

TABLE 4.1 Correlation Values

a) Toyota Correlations

Toyota Profit

Toyota L Productivity

Toyota K Productivity

Toyota M Productivity

Toyota TPM

Toyota Employees

Toyota Output

Toyota Profit

Toyota L Productivity

.865**

Toyota K Productivity

0.549 .703*

Toyota M Productivity

.780** .800** 0.174

Toyota TPM

.849** .891** 0.344 .983**

Toyota Employees

.860** .744** 0.353 .794** .836**

Toyota Output

.949** .879** 0.5 .839** .899** .946**

**. Correlation is significant at the 0.01 level (1-tailed).

*. Correlation is significant at the 0.05 level (1-tailed).

b) Honda Correlations

Honda Profit

Honda L Productivity

Honda K Productivity

Honda M Productivity

Honda TPM

Honda Employees

Honda Output

Honda Profit

0.494 Honda L Productivity

.571* .669* Honda K Productivity

-.705* -0.249 -.676* Honda M Productivity

.610* .813** .781** -0.351 Honda TPM

-0.214 0.537 -0.084 0.432 0.074 Honda Employees

0.199 .800** 0.169 0.125 0.415 .887** Honda Output

*. Correlation is significant at the 0.05 level (1-tailed).

**. Correlation is significant at the 0.01 level (1-tailed).


56

The regression equation of log function and Cobb-Douglas production function for gross

output computed for Honda Atlas are

Ln. (Q) = -3.331 -0.234 Ln. (K) + 1.606 Ln. (L)

A = e.-3.331 = 0.036

TFP (Q) = 0.036L1.606K-0.234

For both methods very low values of role of technology (0.036 and 0.0007) were attained,

showing a lot of room of improvement for induction of technology. Low and negative elasticity’s

for capital K showed over injection of capital. Whereas increasing returns to scale resulted as a

whole, giving values of (1.606 and 1.707) for labor, depicted high volumes of returns by marginal

increment of labor.

Table 4.2 Descriptive Statistics

Mean Std.

deviation

n

Ln value added

output

15.0658 0.59355 10

Ln man hours 14.1842 0.38529 10

Ln capital 13.7191 0.89002 10

Table 4.3 Unstandardized Coefficients of Regression

Model Unstandardized coefficients

B Std. error

(Constant) -7.263 1.805

Ln Man hours 1.707 0.164

Ln Capital -0.137 0.071

Notes: Dependent variable: Ln value added output


57

Chapter Summary

In order to determine the prevalent productivity status of Pakistan automotive industry,

productivity status of two major automotive manufacturers were calculated, Indus Motors

(principle is Toyota Motors) and Honda Atlas (principle is Honda Motors). Major reason for

selecting these two companies out of total 3 companies in Pakistan, was the fact that only these

two companies compete in nearly same nature of cars i.e. 1300cc to 1800 cc cars. A detailed

productivity analysis of these companies was carried out over a span of 10 years’ time i.e. 2000 to

2010. As per financial statements of these companies Honda Atlas showed huge losses from 2006

to 2010. Indus Motors showed better results. Computing all partial productivities and total

productivity using formulae as proposed by Sumanth [4], showed that poor capital productivity

was the main issue with Honda Atlas. Cobb- Douglas production function also showed the

opportunity of investing more in labor rather than capital, especially for Honda Atlas.

Chapter 5- Results of Qualitative Analysis

58

CHAPTER 5

RESULTS OF QUALITATIVE ANALYSIS

Lack of research culture in Pakistan and especially in the automotive industry was the

biggest barrier in the way of conducting this research. Automotive industry is technologically

based, and absence of knowledge sharing methodology in these organizations was a huge

hindrance. However, since the researcher himself had been serving in the same industry for the

last 17 years, he was able to convince these respondents for interviews by virtue of personal

contacts and daily meetings with these individuals. Thus, being a participant observer of this

industry a lot of information was gathered very easily. However, in order to avoid getting native,

triangulation methodology was adopted for data analysis, as conceptualized by Webb et al. [109].

In this methodology two different researchers or two different methods for data analyses are used.

Interviews ranging from 15 minutes to half an hour were written, taped and videotaped

(wherever allowed by the respondents). The responses of the survey were gathered and entered

into XL Sheets. This XL sheet data was then imported into NVivo version 10. Imported file was

placed in internal folders. Columns which were to be coded were entered as code-able data and the

rest were entered as categorical data. After complete analysis of the emerging themes, a total of

326 nodes were made with a total of 2440 references.

5.1 Demographic Details

Classifications of the respondents were made for categorical analysis. Out of 40 respondents,

15 were CEOs, 5 were Directors, 2 were COOs, 15 were General Managers and two were DGMs

as shown in Figure 5.1. Thereafter, comparison chart of two variables were made showing the

designation and qualifications of the respondents. Graph is shown in Figure 5.2. It shows that a

majority of CEOs are under metric (specifically from vendor industry), one is F.Sc.,


59

Figure- 5.1 Graph Regarding Number of Respondents, Designation Wise

Figure 5.2 Graph between Designation and Qualification


60

2 are MBA qualified and two are engineers. Most of the General Managers and Directors are

engineers and very few General Managers are DAEs (Diploma holders). This graph also shows

that except for the designation of CEO, all other top management mostly belongs to the category

of engineers. This aspect is understandable considering the requirements and nature of the job that

is highly technical in nature. However, the point of concern is the qualification status of the CEOs

because without top management commitment, it is nearly impossible to implement any latest

management technique or technology. The reason behind this aspect of lack of education at CEO

level is the fact that businesses run in vendor industry is mostly family owned private limited

companies. However, now the people who actually started the business are handing over their

powers to their next generation who are generally MBA qualified and, in some cases they are

engineers as well. This aspect reflects the bright and a better upcoming future of this industry.

Graph was drawn to see the age brackets of the respondents as shown in Figure 5.3. It is

clear from the graph that majority of the respondents are in the age bracket from 43 to 53. To have

Figure 5.3 Graph of Age of the Respondents


61

a further in- depth analysis, another graph between two demographics was drawn i.e. age and

designation as shown in Figure 5.4. According to this graph majority of the CEOs’ are in the age

bracket of 48 to 53, majority of the GMs’ are in the age bracket of 47 to 49 years, while the

youngest GM is 39 years old. The youngest CEO is of 43 years of age, whereas the oldest are in

the age bracket of 60 to 62 years.

5.2 State of Productivity Knowledge

As per the interview guide, the first question asked from the respondents was regarding the

definition, meaning and interpretation of the word productivity. Most of the respondents were not

sure about the actual meaning of the word productivity. While discussing productivity, they were

actually talking about production or quality. The responses of all the respondents were gathered in

an excel sheet and are represented in Table 5.1. Once the responses were analyzed against the

actual sense and meaning of this terminology as explained by International Organization for

Productivity Management, it was found that 92.5% of the

Figure 5.4 Graph between Designation and Age


62

respondents were unaware of the true meaning of this terminology. Apart from the meaning of this

terminology, the respondents were not clear about the actual sense and need of this important

aspect. These results are in line with the research conducted even in the developed nations like

USA, Australia and Europe, as discussed and proved by Sumanth [4]. The results were entered as

a separate variable with two choices, ‘yes’ for the right interpretation and ‘no’ for wrong

interpretation. The pie chart shown in Figure 5.5 depicts the statistics.

In the second question, the following information was asked

“Do you have any productivity measurement, evaluation, planning and an improvement

department in your organization?”

Figure 5.5 Responses about Terminology “Productivity”, Yes for Correct and No

for Wrong Meanings


63

Table 5.1 Responses about Productivity Terminology with Demographics

Respondent ID Qualification Designation Age Q 1: How you define productivity?

PD001 Mechanical Engineer

GM Inventory

54 Productivity means more production.

PD002 FSc CEO 48 Output/input

PD003 Mechanical Engineer DGM 43 More production

PD004 Below Metric CEO 48 Production with minimum rejection

PD005 Mechanical Engineer Director 45 Output/Input,

PD006

Mechanical Engineer GM 47 It is combination of wastages reduction, cycle time and continuous optimization

PD007 Mechanical Engineer GM 56 Productivity means production per cycle time.

PD008 Below Metric CEO 53 Output/Input

PD009

FSC GM 49 Not very important, safety and quality are more

important

PD0010

Mechanical Engineer Director 52 Stock per hour SPH

PD0011 Engineer DGM 45 Output/Input

PD0012 Below Metric CEO 52 Output planned and done

PD0013

Mechanical Engineer

MSC Manufacturing GM 49

Man hour per Vehicle (HPV), less HPV means more

efficiency

PD0014 Mechanical Engineer MSC Engg. Mgmt.

GM 48 HPV i.e. man hour per vehicle

PD0015 Below Metric CEO 51 Not required with quality improvement is made

PD0016 Mechanical Engineer Director 61 It is a cultural issue

PD0017 Below Metric

CEO 52 More output/ Same input (Resources)

PD0018

Mechanical Engineer GM 52 More production for same resources and manpower

PD0019

Below Metric CEO 47 Efficiency

PD0020 MBA CEO 53

Ratio of out to input in the sense input is the sources

available i.e. man, machine, layout, system, produces and output is their best utilization

PD0021 DAE

GM

Productions 42 Improvement in production

PD0022

Below Metric CEO 62 More production


64

PD0023 Engineer CEO 43 With quality more production and less labor

PD0024 Engineer CEO 53 Output/Input

PD0025 Engineer Director 49 Output/Input per hourly

PD0026 Engineer GM 47 Good results from old machinery

PD0027 DAE GM 47 Less resources and more output

PD0028 Below Metric CEO 60 Machine output at 100% efficiency, production calculations

PD0029 Engineer GM 43 Productivity and efficiency gives production

PD0030 Engineer GM 39 Efficiently getting quality products

PD0031 Below Metric CEO 58 cycle time with production volumes

PD0032 Engineer Director 50 Volume base production

PD0033 Engineer Director 47 More production in minimum possible time

PD0034 Engineer GM 45 Efficiently producing goods

PD0035 Below Metric CEO 55 output/input

PD0036 MBA CEO 46 Effective and efficient utilization of resources

PD0037 Engineer GM 45 Better quality of goods

PD0038 Engineer COO 53 output/input

PD0039 DAE GM 51 More production

PD0040 Engineer GM 47 Increased production


65

Responses regarding this aspect were not required to be drawn on any graph because 100%

respondents replied with “NO”. There is not a single organization in Pakistan automotive industry

which has a complete system of productivity measurement, evaluation, planning and improvement

department, as per the research and knowledge of the researcher. In very few organizations,

maximum evidences found were existence of either some measurement or productivity

enhancement practices under a department.

When the respondents were asked if their organization has hired any individuals for

productivity enhancement related jobs, similar results were found and 100% ‘No’ was received to

this aspect. However, some respondents gave very alarming answers for example; one of the

General Managers, who is an engineer, was of the opinion that “Quality department do the job of

productivity enhancement”. Another respondent who is Director of a company said “productivity

enhancement is the job of quality department”.

One senior official of a large car manufacturing company in Pakistan, who is an engineer,

responded that productivity is looked after by PPC department in their organization. One GM

responded that KAIZEN is for everyone. All these responses indicate ignorance of the top

management of Pakistan automotive industry regarding ‘productivity’ which is one of the most

important aspects of industry. If top management is not so sure, then we can well imagine how

well the complete workforce of these organizations would be as far as productivity enhancement

is concerned. These results depict the actual picture and reasons for the present state of productivity

of Pakistan automotive industry, as measured and shown in chapter 3.

As for question No. 4 from the interview guide, the question asked from the respondents

was:-

“How productivity is measured in your organization?”


66

Results obtained were similar to the ones as received in question no 1. Some of the responses

received are given in table 5.2.

Table 5.2 Responses Regarding Productivity Measurement Methods Used in These

Organizations

Q 4: How productivity is measured in your organization

“More Production less input”

“Production per hour”

“Time cycle, parts per minute”

“Output/Input, It is Capacity depended, Capacity utilization”

“It is combination of wastages reduction, cycle time and continuous optimization”

“Cycle time, as per time and motion study”

“Output/Input and Cycle time”

These responses were analyzed with the internationally recognized productivity

measurement methodology as explained by Sumanth [4] and also in accordance with the

methodology proposed by International Productivity Organization (IPO). Results are shown in

Figure 5.6. It was found that in these organizations, productivity measurement practices were

slightly better than the understanding of the productivity terminology (as found from responses of


67

Figure 5.6 Responses %Age of Correct and Wrong Measurement Methods

question no 1). Pie chart depicts that 17.5% responses were in line with the world measurement

methods, and 82.5 % responses were totally different or opposite from these standards. These

results portray that most of these organizations do not have accurate method of productivity

measurement in their systems.

5.3 Coding of the Survey Responses

After carrying out the analyses of these first four classifying fields, analyses of the code -

able fields started. The development of the nodes started from this step. As per Corbin and Strauss

[108] and Neumen and Neuman [111], this step is nominated as open coding. In open coding, the

data is segmented into different themes and categories [112]. These data segments are different

concepts which emerge and are stored into Nodes, which in NVivo are the storing bins for these

concepts [113]. In this process an analyst tries to understand in detail the meaning of the data

gathered. This complete process is known as coding.

For open coding, there are several different techniques and methods available in NVivo

version 10. First auto coding was applied because this feature is available for data in spread sheets.

This Code in NVivo features allows several node classifications in seconds. Secondly, nodes were


68

made as per number of respondents. Forty nodes were built as there were forty respondents.

Another set of nodes was built as per number of questions asked i.e. 11.

Then coding of the data was done for all code-able columns. All the responses for one

particular question were chosen and all possible nodes were made. Methodology of tree nodes was

adopted to converge the emerging themes into hypothesis and ultimately, into theories. For

analysis of the data, several different options and tests available in this software were utilized. The

option of making new nodes and coding the theme on existing nodes are the options which let the

analyzer subsequently to do open coding with some stages of axial coding simultaneously. Using

the constant comparison methodology, as suggested by Glayser and Strauss [114], allows a

researcher to code or un-code the themes under different nodes as deemed appropriate, which

resulted in refinement of analysis. In order to carry out most accurate coding, the two query

commands TSQ “text search query” and WFQ “word frequency query” were used. With the help

of these two commands, one can very easily explore the data set and can start making nodes

swiftly. Once text query is run e.g. for a word “wastage”, the analysis shows where and in which

context this word has been used, how many times it is used and who used it. Summary of the same

can also be seen in the results. The most effective advantage of this query is the results in the form

of WORD TREE. The results are shown as in Figure 5.7 and 5.8, in which the complete linkages

of the word with said sentences are shown in the form of word trees. These results helped in

understanding the complete context in which the word was used.

To further explore the data word frequency query was run. This analysis tool gives four

types of results. As a sample, results of these tests run on Question 8 are shown on these pages. In

this question, respondents were asked about the difficulties they faced in implementation of latest

productivity enhancement techniques. In the results, word frequency query test gave a complete


69

Figure 5.7 Word Tree for Text Query Search of Word “Wastage”

Figure 5.8 Word Tree for Text Query Search of Word “Kaizen”

summary of the words used in the responses. Sample of this summary is shown in Table 5.3. All

the words used with length count and weighted percentage were given. In the last column similar

words are also given. In this table, results of the problems faced in automotive industry have been

analyzed. The results show that most respondents believe that training, education, resistance and

lack of skilled manpower were the major problems faced by the industry in implementation of the

latest techniques and technologies. Second results achieved from this test were TAG CLOUD.

Results of tag cloud are shown in Figure 5.9. All the words which were mostly used by the

respondents are shown in this tag cloud. The words and terminologies which are more emphasized

by the respondents are shown in the bigger sized font. The results of tag cloud are in line with the

results given in the summary of the test i.e. most of the respondents believe that training, education,


70

resistance and lack of skilled manpower are the major problems faced by the industry in

implementation of the latest techniques and technologies.

Table 5.3. Summary of All the Words Used With Count and Weighted Percentages

Word Length Count Weighted Percentage (%)

Similar Words

Training 8 153 10.52 trained, training

Education 9 114 7.84 educated, education

Less 4 95 6.53 less

Resistance 10 88 6.05 resistance

Problem 7 56 3.85 problem, problems

Skilled 7 54 3.71 skilled, skillful

Change 6 45 3.09 change

People 6 42 2.89 people, peoples

Workers 7 36 2.47 worker, workers

Required 8 33 2.27 required

Manpower 8 26 1.79 manpower

Implementation 14 25 1.72 implementation

Cultural 8 24 1.65 cultural, culture

Staff 5 22 1.51 staff

JIT 3 18 1.24 JIT

Low 3 18 1.24 low

Persons 7 18 1.24 person, persons

Level 5 17 1.17 level, levels

Vendors 7 17 1.17 vendor, vendors

Proper 6 15 1.03 proper, properly

Inventory 9 14 0.96 inventory

One 3 14 0.96 one

Advanced 8 12 0.82 advanced

Due 3 12 0.82 due

ERP 3 12 0.82 ERP

Hiring 6 12 0.82 hiring

System 6 12 0.82 system, systems

Techniques 10 12 0.82 techniques

Lack 4 9 0.62 lack

Pakistan 8 9 0.62 Pakistan

Possible 8 9 0.62 possible

Mind 4 8 0.55 mind

Set 3 8 0.55 set

Sigma 5 8 0.55 sigma

Six 3 8 0.55 six

Stock 5 8 0.55 stock

Constraints 11 7 0.48 constraint

Available 9 6 0.41 available

Biggest 7 6 0.41 biggest

Build 5 6 0.41 build

Centers 7 6 0.41 centers


71

100 advanced? afford allied available the biggest breakdown build capacity centers certain

change ckd concepts constraints cost cultural custom days double due to

education effective environment erp excessive expensive

failed find finished ????? Pakistani people press the problem. Proper

raw ready reduced required resistance roads set shifts shop

sigma six skilled staff start stock stops system systematic techniques

training transformation uneducated used vendors want

workers wrong yes zero

Figure 5.9 Tag Cloud Results: The Words and Terminologies which have been More

Emphasized by the Respondents are Shown in Bigger Size Font


72

5.4 Prevailing Best Practices in the Industry

The step of Question No. 5 was the starting point of coding, since Questions Nos. 1 to 4 went

into the categorical data. Question number five asked:

“What productivity improvement practices have been adopted in your organization?”

This is one of the richest data filled area. A lot of respondents reported several different

types of productivity improvement practices which they thought that they were following in their

organizations. One of the respondents who is General Manager Foundry of an automotive

organization informed that

“Yield increase is used for productivity enhancement as only the good quality raw material

results in better output/input ratio. For productivity enhancement we carry out optimization

studies. We have observed that extra facilities like free food for employees and accommodation

results in far better production outcome from the same labor”.

Another respondent who is Director of an automotive firm reported:

“More capacity utilization is the best methodology for productivity enhancement. We have

to study the operations sequence what is the bottle neck and accordingly, go for the line balancing.

Where ever required we have to, we add machines and add people.”

Open coding of this column resulted in 61 nodes with 28 parent and 33 child nodes and

132 references. First, all terminologies were open coded and then several nodes were made as child

nodes as they were resulted from the same theme. This step is described as axial coding by Corbin

and Strauss [108]. Constant comparison methodology as suggested by Bryman and Bell [107] were

used for axial coding as only this methodology ensures that similar and alike themes are grouped

together. All these nodes were then imported into a folder with title “Used productivity

enhancement techniques” for further analysis and constant comparison. This folder was saved in

the nodes folder.


73

Similar practice were done with Question No 6, which asked

“What latest technologies have been adopted in your organization?”

Generally replies from most of the respondents made it clear that the word ‘technologies’

refers to the latest new machines. For example, an MBA qualified CEO of an organization

answered:

“CNC’s and some automation of the processes……..”

Whereas, some of the respondents also highlighted management issues related to

technologies. For example, one of the respondents who is a General Manager Plant and an engineer

by qualification, replied:

“ISO Certification is good for all purposes, Six Sigma and ERP are too expensive for us.”

One of the General Managers from OEM car manufacturing firm replied:

“Automation is less as we have fool proof systems which result in less accidents due to

POKA YOKA. We have Robots for Wind Screen fitment and have testing lines.”

A CEO of an organization was of the view that:

“No Automation is required only CNC machines are good, old copy lathe give low cost

and more production.”

44 nodes resulted from this question out of which 39 were parent nodes and 5 were placed

as child nodes, with a total of 79 references. No further axial coding was found possible due to the

diverse nature of the respondent themes. All these were saved in a folder named “Used latest

technologies” for further analysis and review.

In Question No. 7 prime players of the game were asked advice on the main theme of this

research:


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“According to you, which are the best suitable practices for Pakistan Automotive

Industry?”

Answer to this question resulted in a total of 46 nodes, out of which 12 were parent nodes

and 34 were child nodes with a total of 169 references. The two major themes that emerged having

convergent views by almost all of the respondents were “optimization” and “human resource

issues”. 57 references were linked with the parent node of “optimization”, having the maximum

frequency. Under this theme the most referred and emphasized productivity enhancement

methodology for Pakistan Automotive industry of Pakistan, as far as these experts are concerned,

is “Wastage Reduction” having a count of 21. One of the General Manager Plants, of an

organization was of the view that for productivity enhancement required elements are

“Continuous improvement, flexible manufacturing and optimization techniques which can

give wastage reduction …..”.

General Manager Productions of another company who is a mechanical engineer

accentuated that for productivity enhancement, certain techniques have to be adopted:

“Time and motion study, optimization, wastage control, and rejection which is hidden by

employees we have to unearth it ………”.

The second most emphasized point was layout improvement, which was referred to on 12

times. A CEO of a company, who is an engineer by qualification, stressed that for productivity

enhancement things to be looked after are:

“Machinery selection, TPM, quality maintenance, layout of Machinery (with time and

motion study)……….”

All these aspects suggested by the experts of this field were in line with their views that

they use the same techniques in their factories and plants, as shown in the answer of Question No.


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5. However, the second most prominent field which was highlighted in their opinion as the most

suitable productivity enhancement practice for Pakistan’s industries, was to resolve the human

resource issues, having 40 references. This aspect will be discussed in detail in the succeeding

paragraphs. However, an important gap to be identified here is that once their answers were

compared with what they actually do in their own organizations, as there is a total divergence

between the two. It means that they never agreed that they are looking after these human resource

issues in their organizations once asked in Question 5, but they strongly suggest that these human

related issues cannot be resolved without looking into these aspects. This was one of the most

important findings that helped in suggesting and finalizing the productivity enhancement model

for this industry.

For example, one COO of an organization gave the following opinion:

“…….trained staff which can stay for long is required then quality systems can be applied.

Wastage control and layout changes are required but talented officers are required who are well

educated to do this task”.

General Manager of an organization replied:

“First of all we need trained and skilled workers who can apply these practices for that we

have to take care of our manpower………”.

Apart from the aspects of training of the employees and availability of skilled manpower,

another aspect which emerged as the strongest point tinted in the opinion of these experts was Job

Satisfaction of the employees. This aspect was the strongest solution suggested by most of the

respondents. One of the General Managers pointed out following points as solution:

“.…ensuring process capability, skill enhancement, training technical people, hiring

educated people like engineers and taking care of HR by ensuring Job Satisfaction”.


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Another General Manger pointed out that in order to enhance productivity, we should be:

“……..enhancing morale by free lunch, taking care of them, providing transport facility,

and providing safety measures will result in better profits”.

12 of the respondents underlined the issues of TQM implementation instead of TQM

certification. They also emphasized for implementation of ERP and modified JIT, for productivity

enhancement of these firms. The respondents highlighted very enlightening issues when they were

asked about the difficulties they faced in implementation of these techniques in Question No. 8.

The question narrated:

“What are your experiences in implementation of these latest techniques and practices in

your organization?”

A total of 23 nodes were made with 11 parent nodes and 12 child nodes with 90 references.

65% of the coding done was converging on one main theme “Human resource resistance”. Under

this parent node the major child nodes were; resistance due to less educated manpower, resistance

due to less training, resistance due to unskilled manpower and resistance to change. Vendor

limitations and issues with the JIT methodology were also discussed.

A General Manger responded to this query as follows:

“Resistance to change is a result of less education level. This can be reduced by imparting

training and hiring skilled workers”

Another respondent who is an engineer and performed the job of General Manager,

responded:

“Skilled persons are required for implementation of advanced techniques and skilled and

educated workers are hard to find in Pakistan”.


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Director of a company who is a mechanical engineer responded to the issue of resistance

as:

“Proper training after that implementation….”

Response of a CEO from vendor company was:

“Very less skilled and trained manpower, less education and resistance from uneducated

people….”

A very important aspect ensued from these responses is that most of the top management

is conceived regarding the core issue in hand, but the point which is not understood is that why

educated people are so hard to find in our country though there is a huge unemployment rate of

educated manpower in this country. This gap identifies a major issue to be looked at, and that is

Knowledge transfer partnership (KTP) between industry and academia. Advanced nations have

utilized this aspect for the betterment of their problems e.g. Singapore. A lot of effort in this regard

are required to address these issues in Pakistan’s automotive industry. A Deputy General Manager

of a company enumerated the following main problems faced in the implementation of these

techniques:

“Vendor industry problem, education, load shedding, environment change and training”

Another major issue highlighted the most, regarding the issues of implementation of the

latest techniques was the limitations of Just- in Time- methodology. JIT is one of the management

techniques which has been implemented in almost all of the major OEMs of auto car assemblers

in Pakistan. OEM includes Pakistan Suzuki, Indus Motors (Toyota), Honda Atlas, Millat Tractors

(Massi Ferguson) and AL-Ghazi Tractors (Fiat Tractor). However, one aspect highlighted by most

of the respondents was that there is a need to make changes in JIT in order to implement it in an

effective manner. The terminology mostly used was “Modified JIT”. This modified JIT is


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specifically used in the sense of JIT Inventory. JIT is a concept of Lean Manufacturing, which

attempts for Zero Inventory or at least minimum possible inventory. This aspect has been

implemented in most countries worldwide. However, experts of Pakistan automotive industry

believe that there is a need to modify this concept, meaning thereby that contextualization of the

concept is required for effective implementation of this concept in Pakistan. In order to reconfirm

this point Ethnographic Content Analysis (ECA) as suggested by Altheide et al. [110] was utilized

on the records of these companies. Findings of this analysis showed that companies changed the

inventory levels to meet their requirements. For example, Pakistan Suzuki started with an

inventory level of 5 days but kept on amending it and finally now they keep a stock of 28 days to

ensure their smooth and continuous production. Similar results were extracted from the record of

AL-Ghazi tractors and Millat Tractors. The reason given by the respondents on this issue is that

the vendor industry is not strong enough to support continuous uninterrupted supplies due to

several different reasons like power crisis, vendors cannot keep high inventory levels for OEMs,

infrastructure issues, and off and on issues of non-availability of material prevalent in Pakistan.

A General Manager who is an engineer and have done MSC in Engineering Management

identified the same problem regarding the JIT issue. He stated:

“Less- inventory is a local constraint of JIT, as vendors keep less inventory. Another issue

is CKD loss due to excessive inventory, e.g. Press shop is at least stock so line stops due to

breakdown”.

CEO of a company who is MBA qualified indicated the similar issues regarding JIT

limitations. He exclaimed:

“Problems are there in JIT, a vendor does not maintain stock especially due to financial

constraints and capacity constraints …….”


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A director of a company also highlighted the need of a modified JIT:

“JIT failed, 15 days stock is held now, good roads and infrastructure is required….”

Another CEO of a company, who is also an MBA, very bluntly rejected the implementation

possibility of JIT in Pakistan:

“JIT cannot be implemented properly and zero- inventory is a joke in Pakistan. Due to

certain issues, we have to keep inventory levels both of raw materials and of finished goods”.

Another aspect which was explored in this research was regarding the future planning of

these experts. The question asked was:

“What are the future plans of your organization for implementation of new techniques?”

Strange findings emerged as a result of the fact that most of the experts were concentrating

upon “Automation” instead of the most highlighted issue of Human resource resistance”. After

analyzing the results of Question No. 5 and 6 regarding the methods used and the most problematic

issues faced in implementation of these techniques, it was felt that most of these experts would

elaborate upon these specific issues and give forth recommendations to resolve these issues for

productivity enhancement and profit increases. But unfortunately, the analysis of the responses

showed that although they feel that HR resistances is the most problematic issue; still they are not

even thinking about taking any steps to resolve these sore issues. It is clear from the analysis that

there is a dire need for these influential people of the industry to look into these matters and try to

improve the present scenario.

CEO of a company gave the following foresight of his organization

“Maximum automation and purpose build machines…”

General Manager of an organization who has done mechanical engineering showed his

future plans in the following manner


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“Automation for labor reduction, Specialty orientation for organization”

The last two major queries in the research questionnaire guideline were the use of tacit

knowledge and facet knowledge in the industry and the effects of labor unions in the industry. For

tacit knowledge utilization, the results are shown in Figure 5.10. The light blue color shows that

people believe that tacit knowledge is very important and must be utilized, while dark blue color

shows that people believe that it is of no use. The last question was pertaining to the effectiveness

and usefulness of labor unions in the industry. Figure 5.11 shows that 92.5% respondents believe

that labor unions are not at all useful for production and productivity of an organization, while

only 7.5% strongly believe that labor unions have a strong and positive impact on the productivity

of an organization. Respondents from Indus Motors reported that Toyota has a very strong union

system and that unions have always performed for better productivity of the company.

Figure 5.10 Graph Showing 65% Respondents Agree that Tacit Knowledge is Very

Important and 35% Disagree

Figure 5.11 Graph Showing 92.5% Disagree that Unions are Good for Productivity and

7.5% Agree that Unions are Good for Productivity


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Chapter Summary

In the second stage of research, interviews were conducted from 40 respondents comprising

of CEO’s, directors and GM’s of 26 automotive manufacturing companies. Interviews ranging

from 15 minutes to half an hour were written, taped and videotaped (wherever allowed by the

respondents). The responses of the survey were gathered and entered into XL Sheets. This XL

sheet data was then imported into NVivo version 10. Responses were coded as per the themes that

emerged from the data. After complete analysis of the emerging themes, a total of 326 nodes were

made with a total of 2440 references. Text search query, word frequency query and several coding

queries were run to explore the data and perform open and axial coding. Demographic details

showed most of the CEO’s are above 50 years of age. 92.5 % respondents were not aware of correct

meanings of productivity. Results showed that measurement methods for productivity used in the

industry are not as per world standards. 65% respondents agreed that tacit knowledge is important

for productivity improvement. 92.5% respondents believe that labor unions are not good for

productivity of organizations.

Chapter 6- Development of Productivity Enhancement Framework

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CHAPTER 6

DEVELOPMENT OF PRODUCTIVITY ENHANCEMENT

FRAMEWORK

6.1 Exploring the Data

In order to explore the data, coding is done in three stages i.e. open coding, axial coding and

selective coding [108]. In the previous chapter, detail methodology of open coding which was done

in this research was explained with few steps of axial coding. In this chapter, further elaboration

on axial coding and selective coding conducted for this research are being discussed with the

ultimate aim of theory generation. One of the major criticisms on grounded theory methodology

is that researcher and analyst always try to do conceptual analysis instead of trying to generate

substantive or formal theory [112], [115], [116]. Hutchison, Johnston and Breckon [117] explained

that a lot of research has been conducted using grounded theory method, but researchers have

failed to inter-relate concepts in order to generate a theory from which the hypotheses can be

generated. Another major criticism of using grounded theory with CAQDAS like NVivo is that

researchers try to fit their research data into computer software instead of using software as a help

for analysis [118]. In order to avoid all such mistakes proper iterative procedure and systematic

constant comparison techniques of data collection and analysis were adopted as explained by the

experts of the field [107], [108], [114], [116], [117]. In this procedure analyst oscillates between

the concepts and categories in order to explore the data for all new possibilities.

Starting from open coding and going towards axial coding is a process in which analyst tries

to go from thick descriptive data into micro analysis of the data [108]. This process was adopted

in the analysis to get the most accurate outcome of the data. In this process, memo making is one

of the helping technique which was persistently utilized for analytical ideas. NVivo gives options

of memo making throughout the process. These memos helped in exploring and understanding the


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data. These memos were used in conjunction with the field notes taken during the participant

observation. Axial coding is named such, as the concepts included in the categories are checked

and rechecked around the axis. There are several different tools available in NVivo to facilitate

this analytical process. One of the techniques is using tree nodes. NVivo give options to organize

the data in the method as shown in Figure 6.1. With the help of this option tree nodes were formed.

This method allows nodes to have more than one dimension. During the constant comparison

method this researcher kept on comparing the concepts emerged and tried to explore in which

category or categories they fit best. However, at tree nodes stage, the categories made are very

broad in nature, so in order to avoid the forceful incorporation of concepts into categories,

Figure 6.1 Screen Shot Displaying Formation of Tree Nodes


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different coding quires available in NVivo were used. These queries and their results will be

discussed and elaborated upon later in this chapter. These queries help in understanding different

dimensions of the concepts and categories.

During axial coding apart from using epistemological methodology ontological stance

(constructive view) was also used. The main reason behind this approach was the criticism on

losing the iterative approach during this process [116], [119]. In order to do so, several questions

were formed while analyzing the data. These questions were answered with the help of coding

queries run. One analytical question formed was:

“What engineers say about the productivity enhancement techniques?”

The same question was used for diploma holders and different education-level people. To

answer this question, simple coding query was run. Results showed views of the engineers about

the prevailing productivity enhancement techniques being used in Pakistan automotive industry.

Similar different questions were run utilizing these coding queries command to explore and

finalize the sub categories. The main purpose of this axial coding was to place the concepts in the

best-suited categories and sub categories.

Another tool utilized for further in-depth study of the concepts and nodes is coding strips.

As shown in Figure 6.2, “coding strips” command of NVivo gives a pictorial view of the coding

done on the text. It also shows the density of the coding on the text and also depicts how one

concept is coded or can be coded in more than one category. This view also helped in exploring

the themes emerged and their relevant placement in the node structure either as a parent node or

child node. This node tree gives strength for axial coding and selective coding. During the constant

comparison method, another strong tool used in NVivo was development of the node map.

Shown in Figure 6.3 is a node map for used productivity enhancement techniques and technologies


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Figure 6.2 Coding Strips Showing the Coding Details and the Density of the Coding

in Pakistan as per respondents. This node map helped in analyzing the parent nodes and the child

nodes. It showed as to which concepts are formed as part of which categories/subcategories. The

bigger box is for the main category and small boxes encompassed inside are the sub categories and

concepts comprising it. The size of the box represents the importance and strength of the concept

in a category and the color scheme depicts the most empathized and repeated concept emerged

from the responses of the respondents. As in the figure below wastage reduction and CNC are

shown in a different color, which shows their importance. This map shows that optimization is the

major category emerged from the data and in this category the most influential concept is wastage

reduction. Similar steps were utilized for all major nodes.


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Figure 6.3 Node Map Showing the Categories and Sub Categories with Color

Schemes


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The next step in coding is selective coding as explained by Strauss and Corbin [108]. As

axial coding is being carried out, several steps of selective coding are also finalized. As per

grounded theory concept, constant comparison is done throughout the qualitative research analysis,

so until finalization of the results all these coding’s were done simultaneously. Further advanced

queries were also performed including; advanced coding query, matrix coding query, group query

and compound query in order to carry out a detailed analytical process. In selective coding process,

inductive view was used in order to generate theory out of the research. Purpose of this theory

formation in my research was to develop Models from the theory. This theory formation and model

building helped in hypotheses generation as well.

One of the tests used in the process was advanced coding query. This test was run to get

answers of complex question like:

“What do General Managers say about productivity enhancement techniques who are

Engineers (or for all other academic qualifications)?”

“What CEOs or Directors of the company, who are above 50 years of age think, are the

most appropriate productivity enhancement techniques for automotive industry?”

Similar types of questions were used for age gaps and designations for all major themes.

Results of these queries helped in establishing relationships between concepts and also between

categories. This ultimately helped in finalizing the selective coding and ultimately leading towards

theory building. Results showed that wastage reduction, daily improvement practices and process

improvements are the terminologies emerging out as the main themes. Similarly the point of view

of General Managers who are MBA qualified, was investigated. Similar types of questions with

all other designations were also checked. For further elaboration and understanding of the data,

matrix coding queries were also run. Matrix coding query was used as this is one of the strongest


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queries available in NVivo which can actually compare different concepts and themes in the form

of rows and columns giving result in the form of a chart as well. The following question raised

the requirement for running this query:-

“What is the opinion of the respondents of different educational background on

optimization?”

This question arose as optimization emerged to be the most prominent technology which

is graded very high in the data. Results of the query are shown in graphical form in Figure 6.4. The

graph shows that mostly the engineers talk about wastage reduction and KAIZEN, whereas the

diploma holders have emphasized upon CAD/CAM technologies. On the other hand, the MBA

Figure 6.4 Results in the Form of Chart from Matrix Coding Query Showing the

Numbers of Responses on Optimization from Respondents of Different

Designation


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qualified professionals have given more focus upon integrated flexible manufacturing systems

(IFS), a more focused management approach. F.Sc. qualified individuals have discussed more

about Ergonomics and POKA YOKE and below metric respondents have emphasized upon layout

improvement, CAD/CAM and wastage reduction.

Several matrix advanced queries were run to find the actual relationship of different

concepts and categories with each other and for theory formulation. Another strong tool available

for qualitative data analysis in NVivo software is Group coding query. In this tool, two different

nodes can be checked for mutual relationships. Group coding query was run for all major coded

nodes in my data. Firstly, group coding query was run for question number 5 in which it was aimed

to understand as to that what are the mostly used productivity enhancement techniques in Pakistan

automotive industry. Results can easily be apprehended in the form of connection map. Figure 6.5

shows the results in connection map form. The respondents IDs are written on the left side of the

circle, while all the major emerged themes are written on the right side. The more number of lines

falling on one concept shows how many people have emphasized on this concept and what is the

importance of this concept in the specific category. As the results of this query are very complex

to be shown, so a zoom in view of one of the node is taken and shown in Figure 6.6. The view

shows that wastage reduction is the concept which is considered as one of the most important

productivity enhancement technique by the experts of the field. Similar tests were run for all major

researched areas including problems faced by the industry in implementation of the latest

techniques and tools of productivity enhancement. Results are shown in Figure 6.7, Figure 6.8,

and Figure 6.9. In problem faced results, it is eminent from Figure 6.7 and 6.8 that human resource

resistance is the major issue in implementation. The major sub categories of this are resistance due

to lack of training, due to unskilled manpower and due to less educated manpower.


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Figure 6.5 Results of Group Coding Query as Connection Map for Respondents vs Used

Productivity Enhancement Practices

Figure 6.6 Zoom in View for Figure 6.5 Showing the Prominent Concept


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Figure 6.7 Connection Map for Problems Faced in Implementation of Latest Tools and

Techniques

Figure 6.8 Zoom in View of Figure 6.7 showing Three Major Emerging Themes


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Figure 6.9 Zoom in View of Figure 6.7 showing Human Resource Resistance as an

Emergent Theme

These points will be discussed in detail later in this chapter. These group query results are more

helpful in finalization of the coding as well as in theory formulation. From this stage onwards, the

model generation for all the 5 major questions and themes of the research will be discussed.

6.2 Model of Prevailing Productivity Enhancement Practices in Pakistan

Automotive Industry

In the questionnaire guide, there were two separate questions i.e. question numbers 5 and 6.

In both these questions, the respondents were asked about the implemented and utilized

productivity enhancement techniques and technologies as prevalent in Pakistan. Replies to both

these questions were merged for development of this model. In NVivo, once model development

is done it shows linkage between all parent nodes and all child nodes. The result is not a model,

rather it is just a depiction of the linkages between them as shown in Figure 6.10 a. In order to

finalize and develop a model we have to run several different queries as explained earlier in this

and previous chapter. Basing on the results of these several different tests performed, a model was

finalized as explained by Hutchison, Johnston and Breckon [117]. Utilizing these techniques,

model as shown in Figure 6.10 b was finalized. As is eminently clear from the model, there are 7

major categories (techniques and technologies) which effect the prevailing productivity

enhancement in auto industry. Out of these 7 categories only one category i.e. “optimization” has

the major impact on the dependent variable productivity enhancement.


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Figure 6.10a Result of the Model Run Test in NVivo

Figure 6.10 b Finally Developed Model of Prevailing Productivity Enhancement Practices

in Pakistan Automotive Industry


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In optimization, only two subcategories out of 17 sub categories have emerged as more

influential which are wastage reduction and Kaizen. Based on this model, several hypotheses were

generated which are given in the succeeding paragraphs.

Hypothesis 1a: Optimization techniques have a major impact on productivity enhancement in

automotive industry.

Hypothesis 1b: Wastage reduction and Kaizen are the most used and effective productivity

enhancement techniques in Pakistan automotive industry.

Hypothesis 2: Using better equipment i.e. latest machines and better testing equipment will

result in productivity enhancement.

Hypothesis 3: TQM systems especially ISO certification will result in better productivity.

Hypothesis 4: Some automation of the processes will enhance productivity.

Hypothesis 5: Modified JIT is more effective for productivity enhancements in Pakistan.

Hypothesis 6: Imparting training will result in better human resource utilization which will give

higher productivity gains.

Hypothesis 7: ERP implementation in Pakistan automotive firms results in better productivity

enhancements.

6.3 Model of Best Suitable Practices for Pakistan Automotive Industry

These respondents were then asked to give their opinion as to what are the best suited

productivity enhancement practices from Pakistan automotive industry. On the basis of the

collected data and utilizing the detailed methodology as discussed earlier, model was developed

as shown in Figure 6.11. As per the model, 8 practices have emerged as the most prominent and

effective for productivity enhancement in Pakistan automotive industry according to these experts

of the field. Two out of these eight techniques have major impact on productivity enhancement.

One is optimization which is very similar to my first model, with one change that layout changes


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have been suggested as equally important and influential methodology by these experts. Secondly,

addressing the human resource issues have also emerged as the major impact practice for

productivity enhancement. In the first model only one aspect came as prominent for better human

utilization and that was training, while in this model three sub categories have emerged which are

hiring of educated manpower, utilization of skilled manpower via training and attaining job

satisfaction of the employees for better productivity enhancements. In this model, Job satisfaction

has shown a major impact on this category. Based on these models, following hypotheses have

emerged from this theory.

Hypothesis 1a: Optimization techniques have a major impact on productivity enhancement in

Pakistan automotive industry.

Figure 6.11 Suggested Productivity Enhancement Model for Pakistan Automotive

Industry by the Experts of the Field


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Hypothesis 1b: Layout changes and wastage reduction have major impact on optimization

resulting in productivity enhancement.

Hypothesis 2: Using better equipment will result in productivity enhancement.

Hypothesis 3: TQM systems have a positive relationship with better productivity.

Hypothesis 4: Better maintenance systems will enhance productivity.

Hypothesis 5: Modified JIT is more effective for productivity enhancements in Pakistan.

Hypothesis 6a: Resolving human resource issues have a major impact on productivity

enhancement.

Hypothesis 6b: Imparting training will result in skilled manpower which will give higher

productivity gains.

Hypothesis 6c: Hiring educated manpower will result in enhanced productivity.

Hypothesis 6d: Attaining higher job satisfaction of the employees will result in enhanced

productivity.

Hypothesis 7: Supply chain management system (SCM) implementation in Pakistan automotive

firms will result in better productivity enhancements.

Hypothesis 8: ERP implementation in Pakistan automotive firms will result in better productivity

enhancements.

6.4 Model of Problems Faced in Implementation of Latest Techniques

Respondents were asked to elaborate upon their experiences in implementation of the latest

techniques in Pakistan. Several problem areas were highlighted which were analyzed and finally

a model was developed showing the most chronic and disturbing issues. Model was developed

utilizing the same methodologies as explained earlier in this chapter. Figure 6.12 shows this model.

In this model, a new concept emerged was vendor limitations. Respondents were of the view that

most of the latest techniques and technologies cannot be implemented accurately in Pakistan


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automotive industry due to several vendor limitations. The aspect of financial constraints of the

vendors was generally emphasized among the limitations. For example, it was reported that due to

financial constraints vendors cannot keep requisite inventory levels at their end which is the

requirement of the OEM, as OEMs like Pakistan Suzuki, Indus Motors (Toyota), Millat Tractors

Limited have tried to implement JIT with zero inventory levels. As vendors do not keep inventory

levels, so zero inventory or minimum inventory attempts by OEMs have resulted in huge

production losses. As a result, these customers have adopted a modified JIT practice. They have

increased minimum level of inventory levels from few days to few weeks. Pak Suzuki has

increased this to 28 day which was initially only 7 days. Similar is the case with other OEMs.

Second major hindrance reported was JIT modification as explained.

Figure 6.12 Model of Problems Faced in Implementation of Productivity Enhancement

Techniques


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The problem which was found to have the major impact on productivity enhancement was human

resource resistance issues as also investigated in the previous two models of my research.

Resistance due to lack of training was found to be the major issue. Prevalence of this concept in

all three models has ensured that this is the highest impacting concept and needs attention. Lack

of educated manpower hiring was found to be the issue having the second highest impact. Lack of

skilled manpower and change resistance prevalent in the manpower were the next two major

concepts which emerged from the data.

6.5 Model of Future Planning for Productivity Enhancement by the

Respondents

Respondents were asked to elaborate their future planning for productivity enhancement in

their companies. Results of this model were very astonishing as several very important issues

highlighted in the first three models were missing. Figure 6.13 shows this model. Several aspects

found were in line with the previously explored and developed models of this research like using

better equipment and implementation of Enterprise Resource Planning (ERP), Supply chain

management (SCM), Toyota production system (TPS) and TQM systems. Existence of power

generation needs is very easily understood requirement considering the prevalent energy crisis in

Pakistan. However, generators are the only focus of consideration for power generation whereas

alternate energy resources can be an excellent option for the industry. Though some respondents

were inclined towards Six Sigma implementation, but majority responded in negative to this

option. The major reason explained by the respondents was that Six Sigma is a very expensive

technique and our industry cannot afford it. This aspect is very much in line with the previous

research conducted, where researchers have proved that implementation of Six Sigma in different

countries like Brazil and India have resulted in big disasters for the companies [63]. One of the

contradicting concepts that emerged was wish and will of the top management to go for maximum


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automation. In the previous three models, same respondents resisted automation however, did

reported that some automation is necessary for productivity enhancement. Pakistan is a developing

country and as per Todoro and Smith [1] for the developing countries, labor intensive methodology

is more suitable as compared to machine intensive or financial intensive solutions. This concept is

in line with the concerns shown regarding the human resource issues in the last three models

discussed. Considering this aspect, it was evident that in future plan model of the same

respondents, the issues of the human resources will be highlighted, which was not the case. Human

related aspects were found missing in the future plan model of the same respondents like; imparting

training, hiring educated and skilled manpower.

Figure 6.13 Model of Future Plans for Productivity Enhancement


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6.6 Comparison with the World Best Practices and Models

All the four models discussed in the preceding paragraphs were the result of substantive

theory. As per Bryman and Bell [107], a theory emerged from the research data and empirical

evidence is called substantive theory, as it was emerged from my research findings. However, in

order to generate formal theory, similar research should be conducted in comparable

circumstances- a method not followed or adopted in this research. However, alternate methodology

of formal theory generation as discussed by Bryman and Bell [107] was utilized according to which

the generated substantive theory is pitched against the already built theory form the literature

review to generate formal theory. For the purpose of formal theory generation, these four models

were than compared with the already established models in the literature. Seven productivity

enhancement models chosen from the literature are discussed in succeeding paragraphs.

6.6.1 UK Productivity Enhancement Techniques

Herrona and Braiden [45] conducted a vast research in United Kingdom on the productivity

enhancement techniques for manufacturing industry. In their research, they emphasized on

utilization of productivity enhancement techniques used in automotive industry worldwide and

suggested the following Model as shown in Figure 6.14. According to their model, 17 practices

Figure 6.14 Productivity Enhancement Model for UK Manufacturing Industry (Herrona

and Braiden 2006)


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are mostly used and are considered as best practices for UK manufacturing industry.

6.6.2 Swedish Productivity Enhancement Factors

Thomas Grünberg [22] conducted a detailed research in Swedish manufacturing

organizations and suggested the major factors contributing to productivity, performance and

profitability. These factors are given in Figure 6.15. He divided the factors in four major categories;

process, overall control, product and resources. He showed his results in a fish bone diagram. He

included a total of 48 concepts which, according to him, are the most important for productivity

enhancement.

Figure 6.15 Productivity Enhancement Factors by Thomas Grünberg [32]


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6.6.3 USA Best Practices Implementation Model

Hallihan, Sackett and Williams [33] conducted a thorough examination of the best practices

successfully used and implemented in the USA automotive industry. On the basis of JIT

philosophy, they explored the most effective techniques which have resulted in productivity

enhancement of these companies. They have suggested an implementation model on the basis of

this research which is shown in Figure 6.16. In this model, standardization, operator centered

quality control and mixed productions are the techniques which have not been discussed in detail

in any other productivity enhancement model made for other countries. Trained work force as seen

in the model is common in nearly all the models of the countries except Pakistan.

Figure 6.16 USA Best Practices Model [33]


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6.6.4 Chinese Productivity Model

A survey was conducted in Chinese manufacturing sector to determine the state of

prevailing best practices and future plans of these companies for better performance and

productivity. Pyke, Farley and Robb [37] reported 16 best practices successfully adopted and

implemented in these manufacturing units, as shown in Figure 6.17. Automated assembly lines

and automation in production have been reported and emphasized separately in this model.

Electronic Data Interchange (EDI) has been discussed in several research works conducted in

china. However, all other computerized concepts discussed in this model as well, like EDI can

be a part of Enterprise Resource Planning (ERP) instead of being addressed separately.

Figure 6.17 Chinese Productivity Enhancement Techniques Model [37]

6.6.5 Indian Manufacturing Improvement Strategies

After studying the productivity improvement models of the developed countries, an effort

was made to study and analyze the top 10 productivity improvements techniques (out of 26 listed)

and the best practices implemented in developing countries. Laosirihongthong and Dangayach [36]

jointly conducted an empirical research on two industrial countries, India and Thailand. In India,


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they conducted survey in 68 automotive companies to find out the best improvement strategies

utilized in these companies. Total Quality Management (TQM) was the technique which showed

the major impact as improvement strategy. Majority of the respondents was of the view that TQM

is the best technique to bring about improvements in automotive manufacturing company.

Amongst these, automation was the least liked practice. Researchers reported that companies in

developing countries were more focused on labor intensive practices than full automation. The

model generated for this research is shown in Figure 6.18.

Figure 6.18 Indian Automotive Industry Best Practices Model [36]


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6.6.6 Thai Improvement Model

As discussed in the preceding paragraph, Laosirihongthong and Dangayach [36] conducted

a research on automotive companies’ best practices for improvement as prevalent in India and

Thailand. The top 10 best practices which were enlisted as a result of survey conducted in 54

automotive companies of Thailand are shown in Figure 6.19. Out of the 26 enlisted techniques the

10 techniques as shown in the figure were indicated by the respondents as most effective while JIT

was thought to be the most effective technique in Thailand.

Figure 6.19 Top 10 Best Practices of Thai Automotive Industry [36]

6.6.7 Thai Technology Implementation Model

In another research conducted on Thailand automotive industry, Laosirihongthong, Paul

and Speece [120] enlisted 15 top successfully implemented improvement techniques in Thailand.

Results of the research are shown in Figure 6.20. Apart from enlisting these top 15 techniques,

these researchers also evaluated and enlisted the major issues and problems faced in

implementation of these latest techniques in Thailand as highlighted in Figure 6.21. Thus one of

the most problematic areas highlighted in Thailand automotive industry was lack of vendor


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capability. This point is in line with the research findings of my research according to which vendor

incapability results in several issues including JIT implementation in Pakistan also. Similarly,

skilled workers issues and resistance from workers as highlighted by them are also in line with the

results of my research. Moreover, over-estimation of utilization, which actually means

underutilization of capacity and capabilities of equipment in particular and of company in general,

is one of the major issues in Pakistan industry as well.

Figure 6.20 Thailand Top 15 Automotive Improvement Techniques Model [120]

Figure 6.21 Problems Faced in Implementation of Latest Techniques in Thailand

Automotive Industry [120]


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6.6.8 Strategic Productivity Improvement Framework

McTavish et al. [44] emphasized that localized productivity enhancement models are not

the only solution to the problems face by the industry. Rather they suggested a generalized strategic

productivity improvement framework. Their framework is given in Figure 6.25. They emphasized

on management techniques generally used in the manufacturing industry for productivity

improvement but they also highlighted the neglected softer issues from the BoK i.e. job satisfaction

of employees.

Figure 6.22 Productivity Improvement Strategies Framework [44]


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6.7 Proposed Productivity Enhancement Framework for Pakistan

Automotive Industry

Sumanth [4] amply differentiated between production and productivity and also

highlighted that the proposed and developed productivity enhancement models, as given in the

literature review, have mainly focused on performance at their core instead of productivity. This

argument started a new field of model and strategies development, specifically focusing on

productivity. In 2005, Tangen gave the concept of PPP model [26], [27]. In his model clear

demarcation between performance, profitability and productivity was made. This study also

triggered several new research paradigms. Researchers all over the world started investigating and

exploring the best practices which could lead to productivity enhancement for a company. From a

generalized scope of manufacturing techniques, researchers started focusing on specific industries.

Automotive industry also received a lot of research and investigation in this field. Researchers [44]

emphasized a lot on generalized models for the world, instead of making localized models. This

kind of strategies showed failure results in industries all over the globe. These results compelled

the researchers to go for local specific or at least country specific improvement models. This

research is also a continuation of these endeavors started all over the world.

As a result of the field survey conducted on the automotive industry of Pakistan and having

compiled the responses of 40 top ranking management individuals of this industry, the following

four models emerged :-

1. Utilized productivity enhancement techniques and technologies Model

2. Proposed productivity enhancement Model by the experts

3. Future Planning for productivity enhancement

4. Problems faced in implementation of latest techniques and technologies


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These models gave a very clear understanding of the prevailing condition of the industry

and also the future plans of the top management of the industry. But once these models were cross-

checked and analyzed, it was found that there were huge gaps between: the prevailing practices in

the industry; the problems faced in the industry, opinion on what should be the productivity

enhancement model of this industry and specially the future plans of these experts. For example

the problem of resistance by the people, non-availability of skilled manpower, less educated work

force and vendor in capabilities were highlighted as the core issues in implementation of latest

techniques and technologies resulting in slag in improvement activities. But very strangely, it was

found that there were no remedial actions against these sore issues in the future plans of these same

individuals. It is believed by the researcher that the core issues that create hindrances in the

productivity improvement must be dealt with as top priority. Therefore, I have included all these

remedies in the proposed productivity enhancement framework of this research.

Secondly, the theory generated as a result of this study was substantive theory as explained

earlier in this chapter. In order to formulate a formal theory, these models were compared with the

already established models in the literature. For this purpose, three models each, developed for the

developed and developing countries were selected. The developing countries selected for the

purpose were India, China and Thailand as all these countries came into being within

approximately similar time frame and have had circumstances quite similar to those of Pakistan.

Furthermore, almost all these countries are also neighboring countries. The close comparison of

these models with developed models of this research gave the final shape to finally proposed

framework.

Figure 6.23 shows the finally generated productivity enhancement framework for Pakistan

automotive industry. This framework looks complicated at first sight, but it actually indicates only


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12 major techniques and technologies which can impact productivity enhancement directly. Other

models in the world generally comprise of 10 to 15 most appropriate techniques for the local

industry. A major flaw indicated in the previous models is that only name of a technique like TQM

is given, whereas TQM is a complete philosophy. Researchers of those studies have not indicated

as to what are the suitable practices, specially focusing on two to three for easy comprehension

and implementation by the industrialists. In this research, apart from giving 12 major techniques

and technologies proposed for the framework, a further detailed description of the sub categories

of these techniques have also been given. These twelve techniques are given below

1. Human Resource Development (HRD)

2. Modified Lean Manufacturing (JIT) and Optimization Techniques

3. Total Quality Management

4. Agile Manufacturing

5. Supply Chain Management System Implementation & Enterprise Resource Planning

(ERP)

6. Total Productive Maintenance

7. Total Productivity Management

8. Computer Aided Design and Computer Aided Manufacturing

9. Partial Automation and induction of latest Equipment

10. Energy Audits

11. TRIZ

12. Autonomous Development


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Figure 6.23 Productivity Enhancement Frameworks for Pakistan Automotive Industry


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6.7.1 Human Resource Development (HRD)

As empirical based results show in this study, human resource resistance is the major

problem in implementing the latest techniques and technologies in Pakistan automotive industry.

Unfortunately, this aspect has not been covered in the future plans model given by these top

management people. In this model the concept of human resource development (HRD) has been

incorporated. Mostly in these organizations the HR department is thought to be responsible of

hiring and firing only. Therefore, important concept of HR development is neglected.

Training has the major role to play in order to overcome the issues of non-availability of

skilled manpower. With training the present manpower can be trained to achieve the desired skills.

Cross training of the individuals is another neglected aspect which has to be incorporated.

Secondly, hiring educated workforce can help resolve the issues. In this industry the strength of

educated manpower is very minimal. In automotive companies especially in the vendor companies

where hardcore engineering is being practiced, problem prevailing is deficiency of and lack in the

number of engineers being hired.

6.7.2 Modified lean manufacturing (JIT) and optimization techniques

“Modified JIT” is another new concept in the findings of this research. Despite intensive

literature review conducted on the topic, researcher has been unable to find any proof of presence

of this term in the BoK. This terminology actually means modified JIT inventory. This concept

has evolved in the past two decades. Organizations of this industry faced several problems due to

low inventory levels as the JIT Inventory explains. Millat tractors (Massey Ferguson), Pak Suzuki,

Al Ghazi Tractors (Fiat) have suffered enormously due to non-availability of spares resulting from

low levels of inventories held. JIT concept explains and desires minimum possible inventory levels

and even claims Zero Inventory levels. This aspect has failed badly in Pakistan industry. Pakistan


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is not very advanced in materials development. Mostly raw materials used for parts manufacturing

are imported. These imports also have flaws that results in a situation when raw materials are very

hard to find or are very rarely available in Pakistan. These shortages of materials during several

diverse times during a year badly hamper production line. In order to avoid this shortage of

supplies, vendors have to keep very high level of inventories so that OEM production does not

suffer. Huge finances are required for this purpose, and there are very few organizations in Pakistan

which have such kind of finances available. This is a major cause of hindrances in supplies owing

to which top management of auto assembler companies complaint about vendor in-capabilities. In

response to these problems, Pak Suzuki increased its inventory stock levels of local manufactured

parts from 3 day to 7 days and then from 2 weeks to now of 28 days. Only this strategy has worked

for Suzuki. Similar findings were reported by Millat and Al Ghazi Tractors as well. This is the

reason why “Modified JIT” terminology has been used. Another reason of short supplies is that

most of the parts manufacturers possess very old machinery and their maintenance systems are

also poor. These problems accumulate and result in line stoppage several times. These down times

also result in short supplies to auto assemblers resulting in production losses and overall low

productivity of the organization. Hence Modified JIT inventory levels have been suggested for

Pakistan in this model.

Another aspect which has been highlighted by nearly all the respondents and also is evident

from the previous productivity enhancement models of other countries is ‘optimization

techniques’. These techniques are less capital intensive and if properly implemented, give

remarkable results. On the basis of empirical analysis, some most prominent optimization

techniques have been suggested in this model. These techniques have emerged as major themes in

qualitative analysis of the data and previous models. These techniques include plant layout


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improvement and work assignment strategy, which enhances productivity with only some minor

changes in the existing equipment and facilities held. Supplier partnering strategy is another

optimization technique which is one of the most neglected areas in Pakistan automotive industry.

Suppliers are not considered as partners rather they are considered as smaller organizations with

lesser importance. This attitude of the assemblers and even vendors to their vendors create big

gaps between these organizations, which result into several quality issues. All these issues can be

resolved and optimization of the capabilities held can be achieved by considering the suppliers as

partners. Similarly, materials optimization is a neglected area, as material is the basic input so

saving material input results in better results. Same is the case with tools and inserts optimization.

Kaizen technique was basically emerged from Japanese manufacturing practices. It is one

of the most adopted and accepted techniques in both manufacturing and services sectors.

Continuous improvement methodology, if inculcated up to the operator level, results in huge

productivity gains. In continuation of this strategy, another technique used is reduction of

wastages. This was the most discussed and emphasized technique in the data gathered from the

respondents of the study. In Pakistan wastage reduction is the most expansive area which needs a

lot of efforts. The famous 7 wastes include: overproduction, waiting, transportation, non-value

added processing, excess inventory, excess motion and defects. The biggest waste in Pakistan

automotive industry is underutilization of capacity. Optimization techniques discussed in this

model will result in elimination of these wastes and will result in better productivity.

Pull system strategy is one of the core strategies of Toyota Production System. In this

strategy, quick change over methodology is used which ensures minimum non-operational time of

the equipment and manpower. Quick changeover means changeover of dies and fixtures resulting

in flexible manufacturing. Minimum setup time is also essential for successful implementation.


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Heijunka technique is also part of this system which means level scheduling. Techniques like these

are not very commonly known to our industry but can make drastic changes with very minimal

cost effect. Proper production planning is essential to implement this technique and get the desired

results. Takt time is another part of this strategy in which process time of each part is set to meet

the production requirements of the complete cell. It is number of minutes consumed in producing

that part as per requirement. This technique is also very accurate and requires no investment.

Similarly Kanban technique is also used which results in pull strategy success.

‘Support the worker’ is a terminology used and adopted in several developed and

developing countries of the world. In Pakistan, giving pay in time, giving food during duty hours

and ensuring accommodation for the workers are the best utilized techniques. There are several

other soft issues which have been neglected in the Pakistan industry. Even several other models

proposed for productivity enhancement in the past do not cover these soft issues of organizational

behavior. In this research, a new addition to the model for productivity enhancement has been

included; the soft issues discussed and proved from the evidence based analysis are job satisfaction

and job security. A lot of research has been conducted in the recent past on the issues of job

satisfaction. Organizations need to promote job satisfaction in their employees in order to prevent

job withdrawal and boost productive performance. Despite proofs and findings of research from

several different countries and cultures, this important aspect of workers job satisfaction has not

been properly emphasized in the prevalent productivity enhancement models. The responses of the

participants and literature survey have proved that ensuring job satisfaction of the workers result

in enhanced productivity. Another major aspect explored is the issue of job security in the industry

as found out during informal interviews of the worker of the industry. It has been found that due


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to job insecurity issues in Pakistan automotive industry, especially in the vendor companies,

workers are not performing at their best resulting into lower productivity of the companies.

Process analysis approach was observed to be the most successfully used technique in some

of these organizations and was producing good results. All organizations need to make use of this

technique because it not only gives remarkable results but is also a cost effective methodology,

considering the fact that finances is a major issue for vendor industry especially. This process

analysis approach is not time bound; rather, it is an ongoing process for continuous improvement.

6.7.3 Total Quality Management (TQM)

In developing countries, TQM has proved to be the most effective productivity

enhancement technique. TQM has been adopted in several organizations but unfortunately the

complete philosophy of TQM has not been implemented in true sense in Pakistan. This is the

biggest drawback in Pakistan automotive industry. It is, therefore, necessary to implement this

philosophy for better productivity. Generally it is falsely understood in this industry that getting

the company ISO certified means TQM implementation. On the contrary, it is a continuous

process, incorporating statistical process control tools and the major concept of quality assurance.

Failure Mode Effect Analysis (FMEA), POKA YOKE (mistake proofing), visual controls and

techniques like 5S implementation are very necessary for quality assurance. In most of the

productivity enhancement models, only TQM word is used without emphasizing and elaborating

upon the techniques which must be incorporated like PDCA cycle. In this model this aspect is

therefore elaborated.

6.7.4 Agile Manufacturing

Lean methodologies have been considered as the most suited practices especially in the

automotive industry all over the world. However, ReVelle [121] indicated that lean techniques are


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old, whereas agile manufacturing techniques are the latest trend setter for productivity

enhancement. He further explained that Agile Enterprise concept is past-lean production paradigm.

Agility is a concept very largely investigated in the recent research studies [54]. This concept has

been discussed in all kinds of setting like services and manufacturing. Agility is concerned with

being flexible enough to accommodate change, explore and also take advantage of the

opportunities posed by the new requirements. Agile practices are basically built on lean practices

with addition of quickness to adopt and accommodate change. The main strategies of agile

enterprise take the enterprise towards being a “niche enterprise”, knowledge based enterprise and

agile (or adaptive) enterprise [121]. Niche enterprise is able to adopt diversity at a quick pace.

Knowledge management is a field which has made an impact on all the fields known to mankind,

and agile philosophy incorporates a never ending knowledge enhancing quest. Being adaptive to

change is the third most important pillar of agile enterprise.

These agile philosophies are the key to success in the prevailing global business scenario.

Researchers have talked about flexible manufacturing in the past but in this model agile

manufacturing and agile concepts have been incorporated. No such precedents were found in the

literature despite extensive survey of the previously proposed productivity enhancement models.

Several agile manufacturing tools and matrices have been proposed to incorporate this agile

philosophy [121]. These tools and matrices are not capital intensive and can give desired results

in a very short span of time. Owing to this aspect specifically, this dimension has been added in

this productivity enhancement framework.

Activity/cost chain is a tool which is extension of activity based costing (ABC). Costing is

a very sore issue in Pakistan automotive assemblers and parts manufacturing companies. Reason

behind this problem is again not hiring educated experts of the field. Very few companies have


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hired ACMA qualified individuals. Mostly costing is done by individuals having M.Com, B.Com

or MBA degrees. ACMA qualified individuals must be hired and they can use activity/cost chains

to resolve the issue. Transactions analysis is another major tool of agile technique which is

interview based studies and research work which highlights how an enterprise is operating. These

tools and concepts are far from even conception in this industry apart from being implemented.

Furthermore, Organization maps can help a company understand the place and relationship

between suppliers and other stake holders of the business. Key Characteristics (KCs) are basically

the most important of the product features which are marked specially to be incorporated for

customer satisfaction. Flexible manufacturing is highlighted specially in this model as this aspect

can enhance productivity of the organizations. By implementation of these techniques, drastic

productivity enhancement can be achieved.

6.7.5 Enterprise Resource Planning (ERP) and Supply Chain Management system (SCM)

The biggest issue observed in these industries was lack of implementation of Enterprise

Resource Planning (ERP) and Supply Chain Management system (SCM) techniques. Most of the

top management claimed that they used these techniques in their industry but the on-ground

verification gave different results. As the researcher was part of the industry, therefore, along with

ethnographic observation, the participant observations were very close to reality. Without naming

these companies here, it can easily be stated that though ERP software is purchased but on-ground

implementation is missing. SCM is used as a name of the department but basic principles and

methodologies which give actual results are far from being implemented in these organizations

except for the foreign collaboration companies like Indus Motors and Honda Atlas. Even in these

organizations, a lot of efforts have to be put in to take full advantage of these techniques.


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6.7.6 Total Productive Maintenance (TPM)

TPM has been successfully implemented in several manufacturing companies of Pakistan

like Pakistan Tobacco Company. As the poor maintenance issues were highlighted by most of the

respondents, therefore it is strongly believed that TPM implementation can drastically improve the

production and productivity of these organizations as proved in literature. It also is a less capital

intensive technique.

6.7.7 Total Productivity Management (TPmgt)

As per the results of this research, it has been explored that there is not even a single

organization in Pakistan automotive industry where Total Productivity Management (TPmgt) has

been implemented. On the contrary, people do not have any knowledge about this philosophy. In

order to enhance productivity TPmgt have to be implemented. It incorporates productivity

measurement, evaluation, planning and improvement practices. Even if TPmgt is not implemented

as a whole at least some productivity department is a must in every organization. Without

measuring, evaluating and planning, productivity cannot be improved which is the core of PPP

model. So it is strongly suggested that every automotive organization must have some people hired

for the job who measure, evaluate and plan productivity improvement. In larger organizations, a

complete productivity department must be incorporated which may require a time span of 2 to 3

years.

6.7.8 Computer Aided Design (CAD) and Computer Aided Manufacturing (CAD)

It has been observed that CAD and CAM methodologies have been implemented a lot but

still there is a dire need to have CAD/CAM philosophy implemented which can further enhance

the capabilities of these organizations. CAD/CAM philosophy is a methodology used successfully

in other manufacturing units of Pakistan like public sector organizations. This philosophy reduces


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the gap between CAD and CAM through which more harmonized production can be attained. This

methodology can be implemented within a time span of two years.

6.7.9 Partial Automation and Induction of Latest Equipment

“Some automation” is the terminology used by several respondents once they were asked

about the prevailing productivity enhancement practices. Full automation is the technique mostly

used in developed countries where a lot of automotive manufacturing plants have been fully

automated. Likewise, several auto parts manufacturing plants have also been mostly automated.

The main reason for adoption of this technology in western settings is owing to high labor rates.

Todaro and Smith [1] explained that developed countries utilize capital intensive technologies due

to more finances available. On the contrary, developing countries mostly focus on labor intensive

technologies, as in these countries financial constraints and low labor rates incline the decision

makers towards these options.

Pakistan is also a developing country so as per this economic theory it is eminent that labor

intensive technologies should be empathized for obvious reasons. Considering these aspects, it is

understood why “some automation” terminology was used by most of the respondents. Even

Pakistan Suzuki Motors (PSMCL), having its principle at Japan, has not installed full automation

in Pakistan as only its Paint shop and assembly line track system is automated. Apart from these

systems, there are very less and partial processes which are automated in the whole organization.

Similarly several auto parts manufacturers have adopted very partial kind of automations.

However, inductions of latest equipment have been found very important and eminent aspect.

Several manufacturers are inducting CNCs and latest test gadgetries like CMM. However, most

successful organizations, especially in China, have very limited investment in expensive

automation machines. These companies invest on economical machines to give them some


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automation. So with less investment, nearly similar results are achieved as can be with expensive

equipment. Timeframe for implementation of this concept depends on the finances available with

the organization.

6.7.10 Energy Audits

In-house power generation is an aspect that has emphatically emerged in the industry in

recent times owing to the prevailing energy crisis in the country. This aspect is essential for all the

industry. Multinational firms like Suzuki Motors have also incorporated in-house power

generation in current financial year. Non availability of electricity is resulting in line stoppage of

these companies for days and days. Hence, in-house power generation capability is a must for

better productivity of these organizations. Its shortage results in low overall equipment efficiency

and plant efficiency. One of the most important aspects before going for in-house power generation

is carrying out energy audit of the company so that energy wastages can be reduced and actual

energy requirement can be computed. This aspect needs a study of 2 to 3 months only.

6.7.11 TRIZ

Innovation and creativity is in the soul of human beings. Unfortunately these aspects are

not given due importance in manufacturing, especially when routine productions and operations

are concerned. TRIZ is terminology invented by Genrich Altshuller, a Russian (1926-1998) who

made several new discoveries in the field and gave numerous tools for TRIZ implementation [121].

TRIZ is Russian terminology, translated as the theory of solution of innovative problems.

Innovation and creativity are two strongest concepts in the core of TRIZ. In order to use innovation

and creativity techniques in an organization, empowerment and freedom of thinking are the most

promising and foremost requirements. Unfortunately, in manufacturing as a whole and automotive

manufacturing specifically, employees have to follow strict orders. This is the main reason that


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not even a single productivity enhancement model proposed in the past, possess these strong

techniques. Mentors of the automotive industry e.g. Henry Ford gave great importance to

innovation and creativity and achieved remarkable enhancement results. Considering these

aspects, it has been suggested in this model that TRIZ should be implemented in Pakistan

automotive industry as a strategy while giving empowerment to the employees at all tiers for

productivity enhancement.

6.7.12 Autonomous Development

Being a participant observer of one of the companies of this industry and being

ethnographic researcher for most of the other companies of the same industry, the researcher

conceptualized that instead of trying to increase the existing R and D section or to establish two or

three of these sections, the best option to adopt is “Autonomous Development”. As per this new

concept, every production section can be given a small in-house team which can develop new

processes and products which are similar to the parts already in production. Actually, a huge

diversity can be seen in Pakistan automotive parts manufacturing companies. A single organization

is producing parts like flywheels, brake discs, brake drums, exhaust manifolds, clutch assemblies,

tie-rod ends for different assemblers. Similarly, one organization is not only producing parts of

casting but is also producing sheet metal and die casting parts. Generally people in the world are

going for specialization. However, in Pakistan not a very large number of auto parts producers

who can produce quality parts consistently are operating, so OEM assemblers are focusing on the

big parts manufacturers only. Owing to this aspect, these parts manufacturing companies are

diversifying continuously to enhance their market shares. Considering this scenario it was felt that

these different sections can be given teams to develop new processes and improve those without

taking help from R & D sections. In-charge of each production section, line heads and operations


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engineers of these sections can actively participate in these development activities apart from

looking after productions. In this way, with very less financial inputs, time to market can be greatly

decreased because specialization of these production people can be utilized in producing new

similar kind of parts and processes. Only one year is required to implement it in complete sense.

Unfortunately, development philosophies are not incorporated in the existing productivity

enhancement models. It is felt that incorporation of this new concept along with existing

development techniques will result in huge productivity gains. It was also established that labor

unions are not playing positive role in these organizations and, as a matter of fact, are having

negative impact on the productivity. Therefore, maximum efforts should be made to either

eliminate these labor unions or their role should be directed towards positivity which will result in

better productivity.

Chapter Summary

Open coding and some steps of axial coding were done in the previous chapter. In this

chapter selective coding was done as suggested by Strauss and Corbin [108] in order to develop

the final theme. For selective coding advanced coding queries comprising of Matrix coding query,

group coding query and coding comparison query were run. The main purpose was to develop

productivity enhancement framework for Pakistani automotive industry. Firstly, with the help of

this methodology productivity model of prevalent best practices of this industry was developed.

Another model was developed to show the problem faced by this industry in implementation of

latest techniques. These models were then compared with the productivity enhancement models

of USA, UK, China, India, Thailand and Sweden. Comparison showed several gaps in the model

followed in Pakistan. One example of the gap was emphasis of Pakistani organizations on ISO

Certification only without proper step by step on ground implementation of TQM Philosophy.

Based on this comparison finalized productivity enhancement framework was developed. Being a

developing country and labor intensive culture the best practices used in the world which require

less capital providing maximum output were suggested. Suggested model was then explained point

wise in order to give the clear picture of the suggestions made.

Chapter 7- Implementation Methodology

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CHAPTER 7

IMPLEMENTATION METHODOLOGY

In the previous chapters, it has been discussed that how productivity enhancement

framework was developed from the survey data collected from respondents. The comparison of

this framework was done with the previously established productivity enhancement models for

automotive industries of different countries and ultimately, a finalized productivity enhancement

framework emerged. In order to validate the concepts of the framework, implementation of these

concepts was done in XYZ company (name of the company is hidden due to secrecy of the

company records. XYZ (Pvt) Ltd is one of the largest auto parts manufacturers in Pakistan

automotive industry that has also been enlisted in Top 100 fastest growing organizations in

Pakistan in 2012. Pakistan Suzuki Motors Corporation and Millat Tractors have given the best

partnership (vendor) award this company several times in past few years. This organization has

revenues in Billions of Rs per annum. Another reason to choose this organization was that the

researcher was closely linked with this company and thus had the leverage to get these techniques

and technologies implemented in real time productions and operations.

7.1 Stage wise Implementation

The proposed framework was implemented stage wise, as this implementation required

complete cultural change. Bringing about such a change in any organization is one of the most

difficult tasks. The biggest challenge faced in this context is resistance from the employees [120]

as also found in the results of the data gathered during survey of this research. Secondly, as

highlighted in chapter 6, top management of these organizations is of the opinion that the biggest

problem faced in implementation of these technologies relates with manpower. Stage wise

implementation will be discussed concept wise in the preceding paragraphs.


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7.2 Human Resource Development

Once the researcher joined this company, the first problem observed was nonexistence of

educated manpower in the required places. Despite being one of the biggest engineering

organizations in Pakistan, it lacked presence of engineers on the shop floor. Hence the first and

foremost step taken was induction and placement of engineers on the shop floor. This is certainly

the most difficult task in Pakistani organizations especially in the vendor industry. Maximum

qualified employees looking after production and operations in these companies are diploma

holders i.e. DAEs. These engineer associates are most powerful people in productions and also

have the maximum strength in number as well as in influence. Several foremen of the production

sections are even less educated. The fear of job security compels them to ensure that people who

are more educated and competent than them should not be hired or, if at all hired, should not stay

in the organization, particularly in their sections. Such organizational politics gives rise to

numerous issues and problems within the organization. Given this scenario, several attempts to

induct engineers on the shop floor failed in the past. Knowing the past history, a complete work

plan was made in order to execute this implementation successfully. The implementation

guidelines and methodology is given in the succeeding paragraphs. Any organization whether

manufacturing or services, can use a similar methodology to bring about successful cultural change

in their respective organizations. Apart from hiring engineers, educated and skilled manpower was

hired at all tiers, right from operators to managers. Previously, the operators hired were mostly

uneducated as they take less pay. After the change of rules, at least diploma holders or people with

some educational back ground were hired in order to ensure better job performance. Similar policy

was adopted regarding supply chain management people and computer operators. These aspects

have to be addressed for better productivity results and it will take maximum one to two years for

implementation.


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7.2.1 Methodology of Engineer’s induction and placement in an organization

Fresh engineers form the newly passed courses should be given priority. This is because

new engineers can easily be adjusted into the organizational culture instead of trying to change an

old engineer. Fresh engineers have the motivation and stamina to forego the agonies of the early

days, especially if the organization does not have engineers as per their previous record. Engineers

with more experience can be hired at a later phase if deemed necessary. In order to retain these

engineers, the organization must hire one engineer as senior level manager to whom they would

be reporting and are looked after.

7.2.1.1 Introduction Stage

Introduction visits needs to be arranged for engineering students. The best way to do this

is to collaborate with main engineering universities in the area and invite them for industrial visits.

As a general practice, most of these institutes also write continuously to the organizations and

request for the permission to bring their students for such visits. Internships requests from the

universities should be entertained and at least two engineers must be doing internship in the

organization as frequently as possible. These internees can be assessed very easily during this

period and can be offered a job if found competent and hardworking. This way the whole costly

process and exercise of hiring, interviews and induction can be eliminated. Still if requirement

arises, proper hiring procedure can be undertaken and engineers can be interviewed and hired on

three month probation period.

7.2.1.2 Appropriate Strength

If engineers have not been hired in the organization previously, at least a group of 3 to 4

engineers should be hired. This group can be a mix of mechanical, mechatronics, electrical and

electronic engineers in accordance with the requirement of the company. The reason for this group


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concept is that single engineer runs away if left alone. Group activities give them strength to face

the difficulties posed by the shop floor individuals, workers and foremen. All efforts must be made

not to hire a group from the same class and if possible not from the same university, at least in the

beginning.

7.2.1.3 Diffusion Methodology

Smooth diffusion of these engineers (trainees) into the existing system may be ensured in

two phases.

Phase I

1) An extensive on job training of 3-6 months (depending upon the tasks assigned,

which will require continuous evaluation).

2) No authorities to be delegated to the trainee engineers in Phase I.

3) Trainees should work under the supervision of floor managers or shop floor

supervisors, who will be responsible for their effective training.

4) Trainees must work on the machines with their own hands.

5) Working with their own hands does not necessarily means producing parts on

regular basis like machine operators; rather this practice should be taken as an

exercise for better understanding of the procedures and processes of

manufacturing.

6) While working on the shop floor, trainee engineers must closely interact with the

working staff and floor managers to enhance cordial relationships and understand

their problems and agonies.

7) Under no circumstances should the trainee engineers get harsh or try to show

bossy attitude to the staff/floor managers.


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8) In case of any problem or unwanted situation, trainees must report to Senior

Engineer hired at the post of Manager or General Manager for guidance and

support to solve the issues at hand.

9) Trainees must always have a note book and a pen and must take notes of any flaw

or unwanted activity in the processes. They should endorse some suggestions for

improvement of processes every day.

10) They should submit summary of daily notes to the senior engineer.

11) Progress of these trainees should be monitored continuously. They should be

given assignments on regular basis e.g. downloading details about the machine

and processes the trainee is working on, making operating procedures of the

machines and processes in witting, drafting list of safety checks/ precautions to

be ensured in a process etc.

12) Based on these points they would be giving a presentation to the Board of

Directors/ Director or senior management on weekly basis for the first month and

after that on monthly basis.

13) Rotation of trainees into different departments should be monitored by senior

engineer personally.

14) Before sending these trainees to any department, floor managers must be briefed

personally by Board of Directors/Director about the need and advantages of

having these engineers in our organization. (The main reason for this practice is

to curb any tendency of retaliation or negative impact about this most wanted and

needed addition).


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Phase II

1) Trainee engineers can be given the post of Operation Engineer of minimum 1-2

departments after completion of first 3 to six months (depending on the

complexity and nature of the job).

2) First pay increment should be authorized at this stage.

3) Trainee mechatronics and electrical engineers can be given the responsibility of

establishing an in-house repair and maintenance department of CNC machines,

and subsequently given the role of repair and maintenance engineers.

4) Trainee mechanical and industrial engineers must be given production sections

and they must report on the continuous improvements done in their sections.

5) Job description/job design should be finalized before the end of the stipulated

training period.

6) On completion of one year period these engineers should be promoted to the

appointment of assistant managers. After another two years time they can be

promoted to the appointment of deputy manager. On completion of 6 years they

can be given Manager Post.

7.2.2 Training

Training is mostly thought to be an activity for the beginners especially in Pakistani

organizations. However, this is the biggest misconception, as training is an ongoing process for

every individual of an organization from top to bottom. For new induction at any appointment in

an organization, people do tend to train and guide the individual but as the time passes everyone

starts believing that they do not need any training any more. This aspect was specifically

concentrated upon. Apart from the on job training of the engineers and other work force and staff


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special training sessions were run. Some training programs were conducted in- house and some

were outsourced. For engineers and operators, CNC programming training was most beneficial as

it gave instant results in the shape of better production, better efficiency of manpower and machine

and better quality products hence resulting into better productivity. Trainings of 5S

implementation, Kaizen methodology and layout improvements techniques also resulted in

marvelous results. Engineers were also given the opportunity to attend management courses from

best reputed universities in the evening on company expenses. Foreign tours to world re-known

manufacturing companies were conducted to learn the latest manufacturing techniques. Training

of computer operators was also carried out for better performance.

7.3 Modified JIT and Optimization Techniques

Modified JIT terminology has been discussed earlier in chapter 6 as well. Modified JIT

specifically refers to modified JIT inventory levels. JIT philosophy is advocate of zero inventory

levels. Nearly all big automotive assemblers and several auto parts manufacturers have

implemented JIT philosophy in Pakistan, but no organization has been able to achieve zero-level

inventories. The major reasons as explained earlier are: material shortages, poor infrastructure of

the roads and other communication means and non-capability of the vendors. Considering the

experiences of these organizations for past 20 to 30 years it is quite evident that every automotive

manufacturing or assembling unit in Pakistan has to adopt modified JIT. The inventory levels for

these companies now range from 15 to 28 days at least. Similar is the case with JIT manufacturing

for the similar reasons.

Optimization techniques were the terminologies most discussed and emphasized upon by

the respondents of this research. Almost all the respondents were of the view that the first and

foremost activity to be performed for productivity enhancement in Pakistan automotive industry

has to be use of optimization techniques. Several different terminologies and concepts were


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discussed by the respondents regarding optimization techniques. Wastage reduction was the most

prominent one amongst them. It is generally believed that wastage reduction can drastically

improve the productivity of any organization. This aspect has further been strengthened by proofs

in the literature review about the issue. Existence of this technique in nearly every productivity

improvement model further augments the belief. Wastage reduction is very less capital intensive

and can give substantial results. Therefore, considering these points, several wastage reduction

techniques were used for productivity enhancement. Layout improvements are among the

optimization techniques which are believed to be the key in wastage reduction and productivity

improvement.

Most of the auto parts manufacturers in Pakistan grew from very small enterprises to

SME’s, while some have grown up to the size of large organizations. As these organizations started

from very small setups, their growth varied from time to time as per the market demand. For all

the growth stages, new machineries were added over a span of time without changing the layouts

of older machinery and equipment. This led to haphazard placement of the machinery and

equipment. Similar was the case at XYZ Company and several other auto parts manufacturing

organizations which were personally visited by the researcher. The international auto assemblers

like Toyota, Suzuki, Honda, Millat Tractors, Al-Ghazi Tractors and MEL had better plant layouts.

But it was felt that even in these plants a lot of older techniques are in practice and there is a dire

and urgent need for immediate improvement and better results. Most of these plants were planned

and established in last 80’s and big improvements has to be done in these plants as well.

Detailed process analyses of all the products manufactured at XYZ Company were carried

out to determine the flaws and bottlenecks. During these process analyses, it was found that a lot

of time and energy is wasted due to poor layouts. The machines are not placed as per the operations


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to be performed on the products. Rather in due course of time as the machines were added those

were placed wherever the space was available. As a sample study, one section of this organization

will be discussed. The previous layout of the specific machines will be shown and discussed, and

then the new improved layout with benefits will be listed. The results of all these activities will be

discussed at the end.

The section which has been taken as a case study is named as flywheel section. This section

comprises of CNC machines (i.e. CNC Machining Center 3-axis and 4-axis, CNC turning /lathe)

and induction machines. All parts manufactured in this section are critical and require high

accuracy at the customers end, as these parts are supplied to OEM’s (Pak Suzuki, MEL, MTL and

FIAT). The parts being manufactured in this machining cell include fly wheels, brake drums, brake

discs and exhaust manifolds. Furthermore, oil pump and water pump of tractors are also

manufactured in this section. Several components like flywheels are single source components as

they are manufactured only in this organization for some of the make and type of cars

manufactured in Pakistan. The layout of this machining cell was functional type and all machines

were placed in the cell randomly. Owing to this unplanned layout, large number of problems used

to arise during production that caused rejections and also led to customer complaints. The problems

faced include following:

Time wastage

High work-in-process inventory

High labor cost

High rate of rejection

Parts mixing

Less Production


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High parts movement within the cell

High Operator’s Fatigue

High Customer Complaints

The old layouts are shown in Figure 7.1 (a, b, c and d). The figures depict that these

placements were adding up to the issues as enumerated in the preceding paragraphs. Process flows

of these components are shown in blue and green colors. In order to overcome the above mentioned

problems, layouts of the manufacturing cells were changed. While developing and improving the

proposed layouts, the foot print areas of machines were taken according to perfect scale and total

shop floor space was measured. During the setting of machines sequence, the ergonomics and

cellular manufacturing concepts were incorporated. Time and motion study and work study of each

machining operation was done accordingly. The concept of Heijunka technique (level scheduling),

pull strategy, takt time methodology, quick change-over time methodologies were kept in mind

while finalizing the new proposed layout in order to achieve the benefits of these techniques. In

order to eliminate the 7 wastes, every location of the machines was drawn on AutoCAD and finally

a complete model was finalized as shown in Figure 7.2. Before changing the layout, a buffer stock

of spares of 14 days, manufactured on these machines, was maintained. All machines were

removed and after ensuring 4S of this area, marking was done on the ground and machines were

placed as per the planned layout.


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Figure 7.1 a Old Layout of Flywheels Manufacturing

Figure 7.1 b Old Layout of Brake Drum type X Manufacturing


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Figure 7.1 c Old Layout of Brake Disc Manufacturing

Figure 7.1 d Old Layout of Brake Drum type Y Manufacturing


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The whole exercise took only two days and production on these machines started on the

third day. New layout is shown in Figure 7.2. Comparison of the old layout and the new layout

shows the remarkable difference. In Figure 7.3 zoom in view of the flywheel production line and

brake disc production line is shown. The new positions and old position of the machines are shown

with the help of arrows and circles. The upper line is of flywheel machines. The two and fro

movement of the in-process components are evident from the old layout. After first and second

operation, parts used to be taken to induction machines and after the ring fitment these were again

taken back for fourth operation. This was a complete waste of time and efforts and also resulted in

quality issues. Now, under the new arrangement, these machines are placed as per the operation

sequence as shown in new layout, resulting in minimum possible travel of parts with lesser

manpower required. Another thing added was trolleys, with which instead of picking up and

carrying, the items are now easily passed to the next operation resulting in lesser fatigue for the

workers as well. Similarly, machining centers were placed far away from the operations

requirement owing to which the to and fro movement was too much. Now, under new arrangement,

from first to the last operation all the machines are placed in line and smooth operations results in

better quality and improved productivity. Similarly in Figure 7.4 brake drum section is shown as

per new layout which is in sequential order. Previously these machines were mixed with the CNCs

of flywheel and brake disc operations. The new cellular arrangement results in smooth flow as all

the parts produced are checked, inspected and packed the same day. Still, in the new production

line, batch manufacturing concept is followed along with process analyses techniques in which

bottleneck operations are allowed more number of WIP then the other operation. The logic of this

arrangement is very similar to the modified JIT concept described earlier. Another technique used

while planning the layout was converting several CNC operations to conventional machines


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operations. The main reason behind this methodology is the fact that CNCs are very expensive and

number of parts produced on CNC’s are less due to several small operations performed. Bringing

out the smaller and easier operations on to conventional machinery resulted in increased

production and also higher productivity. Similar exercises were conducted on all the sections and

improved productivity gains were achieved. Several other layouts are placed in annexure C. All

these changes were made in the existing factory.

Apart from all these continuous improvement methodologies, another highlighted area of

support for the workers was also explored and worked upon. First, a survey was conducted in this

company to measure the job satisfaction level of the employees. This satisfaction level was pitched

against the concepts of intension to leave and organizational citizenship behavior. The tools as

discussed in the literature review section were utilized. The results showed that employees were

generally not satisfied due to low pay scales, insufficient annual increments, non-existence of

proper policies and procedures and non-cooperative attitude of supervisors. Therefore, proper

policies were made for attaining enhanced job satisfaction, pay scales of these individuals were

increased during three years from 2010 to 2013 and annual increments from 15% to 35% were

given. Another major issue highlighted in the results was job insecurity resulting into high

turnovers especially for the educated employees. The researcher was not able to fully control this

aspect due to several reasons one of which is that these vendor organizations are family owned

businesses and owners do hiring and firing on frequent basis as per their normal practice. The only

solution for this problem is incorporating cooperate culture in these organizations for which Top

Management is still not fully ready. However, the next generation of these owners are very well

educated hence a change is coming which will take few years to become effective. All these

techniques require at least 2 to 3 years’ time for proper implementation.


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Figure 7.2 New Layout of Manufacturing CNC Section with Latest Techniques Used


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Figure 7.3 Zoom in of Flywheel Production Line and Brake Disc Line

Figure 7.4 Zoom in for Brake Drums Manufacturing Cell showing the Process Flow with

the Help of Arrows


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7.4 TQM Implementation

This organization was not even ISO 9001 certified in 2010, despite the fact that it had been

in operation since 1980s and was also involved in exports. Therefore, as the first step, ISO

certification of the organization was ensured. It took one and a half year to complete this process

during which a lot of documentation was done to fulfill the requirements of the process. This whole

practice improved a lot of processes. This comprehensive exercise was not done for the sake of

getting the certification alone. Rather, proper implementation of the TQM philosophy was done

during this exercise. Generally in these organizations a very ghastly practice done is that most of

the rejections are hidden from the top management and true picture is never shown to them due to

several reasons that among other include job insecurity and fear of getting punishment. Another

reason for this concealment is non-acceptance of any rejection by top management. Therefore, a

lot of effort was done to document every rejection and even every rework. Rework was considered

as part of production. A culture of quality ensuring and producing parts right the first time, was

incorporated. Every rework is a wastage which results in cost of poor quality. The famous 7 SPC

tools were brought into practice to improve the situation.

The case of brake disc is an example to depict the results of these activities. A huge number

of brake disc failures were received from Pakistan Suzuki, one of the customers for one of their

products. In July 2012, a detailed exercise was done to improve the situation and reduce these

rejections to minimum. Proper quality checks along with process improvements were made.

Quality by design concept of Taguchi was utilized and fixtures and processes were modified. The

quality checks were documented and improved. Enormous financial benefits were achieved due to

these exercises.

In Pakistani organizations, the old concepts of quality controls are still generally practiced.

Quality Assurance (QA) acts as an umbrella on quality control as per TQM philosophy. QA was


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established and practices of failure mode effect analysis (FMEA) were made a routine practice.

Inclusion of these practices changed the quality culture of the organization. Visual controls were

added for POKA YOKE (mistake proofing). These visual controls are one of the best tools for less

skilled and less educated manpower in these organizations.

In 2010, the atmosphere of the production line was so disturbing that mostly the visitors

used to avoid going into the production sections due to the fear of getting their clothes dirty or

even torn in certain cases. It was assumed that as this facility as well as the machinery and

equipment is so old, therefore it cannot be improved as far as the environment is concerned. It was

also misconstrued that these workers love to work in dirty environment and does not need to keep

the environment clean. First of all this mindset was changed for implementation of 5S. Long

duration of talks with the workers and the management convinced everyone that the situation needs

to be improved. These discussions convinced the top management that by applying cleanliness

practices and improving the environment, production will enhance and quality of the products

produced will also get better. The entire workforce was empowered to improve their surrounding

as they deemed appropriate. They were rewarded for every incremental improvement made in their

area. This changed the culture and a very leaner environment was achieved with placement of

requisite tools and accessories at their right places with an effort of 6 to 10 months’ time. The

worst practice previously adopted was placement of parts and even finished goods on the floor.

Proper plastic pallets and trolleys were made and fine was imposed for placing the components,

either WIP or finished, on the floor. Cabinets were provided on the shop floor and tools and

accessories which were of immediate use were placed with name tags. All the extra items present

at the shop floor were submitted in the store.


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As per the results of this research, it was found that mostly people believe that Six Sigma

is a very expensive methodology to be implemented in Pakistani organizations. Previous research

done internationally on similar kind of environment also gave the similar results. So it was

conceptualized that instead of investing heavily in Six Sigma, the basic theme and tools of Six

Sigma can be used i.e. PDCA cycle as given by Deming. Plan, do, check and act tactics can be

used along with 7 SPC tools to give an alternative of six sigma and still sufficient satisfactory

results can be achieved. This aspect requires 2 to 3 years for comprehensive implementation.

7.5 Agile Manufacturing

Agile manufacturing is one of the latest manufacturing concepts in the manufacturing

paradigm. This aspect has been discussed in detail in the previous chapter. Agile enterprise concept

has to be incorporated for agile manufacturing. The researcher was unable to find even a single

source in Pakistani organizations that was aware or was thinking about converting to this latest

manufacturing technique. Since this is a totally new area, it was felt that it would be impossible to

convert any organization into agile enterprise. Hence, it was decided that instead of convincing the

management to incorporate agile enterprise concept in the strategy of the organization, utilization

of agile enterprise tools and matrices will be used in the first place. In the auto parts manufacturing

companies one of the biggest flaws observed was nonexistence of proper costing systems. Even

absence of ACMA qualified professionals for manufacturing costing added the agonies in

improving the prevailing system. Mostly MBA qualified and finance people, with very limited

knowledge of manufacturing methodologies, perform costing of the manufacturing activities. In

order to cope up with the system, first of all Industrial Manufacturing Engineering Department

(IME) was established. To the best knowledge of the researcher, this is first ever IME department

consisting of engineers in any of the auto parts manufacturing organizations in Pakistan. These

engineers were taught and trained about activity based costing (ABC) which was then taken to the


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next level of activity/ cost chains, one of the strongest tools of agile manufacturing. One of the

examples of these activity based costing sheets is given in table 7.1. These costing chains resulted

in actual on-ground calculations of the manufacturing cost. This in turn led to price revision cases,

results of which will also be discussed in the validation section. Top management was astonished

to find out that several components were supplied at prices lower than the actual cost of the

component resulting in huge losses to the organization. Therefore, for the parts where OEMs

refused to give proper price revisions, production was stopped and focus was shifted to the parts

giving some profit to the organization. This did affect the revenues negatively but resulted in pure

increase in the profits of the organization. Flexible manufacturing techniques were also

incorporated which resulted in higher productions for several parts utilizing the same machinery.

For this purpose, quick setup times and quick change over time of fixtures were ensured.

Transaction analyses technique was used in which interview based surveys were conducted

to determine the problems areas and to address them. These research based techniques are the most

neglected areas in the understudy organizations. Organization maps and key characteristics

techniques were also incorporated. Having said that, it is pertinent to mention here that agile

manufacturing concept was not implemented with 100% accuracy and still needs lot of endeavors

to ensure better results.


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Table 7.1 Activity Based Costing Example of One of the Component


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7.6 ERP and SCM Implementations

ERP is being used in XYZ Company. Ground Plans were bought back in 2009 but on- ground

verification showed that even the stores were not computerized accurately. Documentation was

mostly done on pages instead of ERP system. For finance department, ERP has given good results

but implementation of ERP in all sections of the organization was a sore point. It was strongly felt

that proper implementation of ERP and SCM was required in order to get optimum utilization of

this expensive asset. This exercise of proper implementation is still under progress and will take

some more time due to lesser top management commitment to the same.

7.7 TPM and TPgmt Implementation

Out of 7 pillars of Total Productive Maintenance (TPM), the concept of Autonomous

Maintenance (AM) is highly valued and considered to be the basis of TPM. This concept was

implemented right from the beginning in the implementation phase. This autonomous maintenance

concept advocates that every operator is responsible for the maintenance of his/her

machine/equipment. This concept gives the powers and responsibility to the operator resulting in

better performance for both machine and labor. In 2011, the maintenance department working for

the conventional machines was dissolved. This was the beginning of TPM philosophy

implementation. The production sections were given the responsibility and powers to undertake

autonomous maintenance of their equipment, whereas the maintenance department was made

responsible for development of new machines and up gradation of the existing ones. This practice

is also partially completed and still needs a lot of efforts and time for proper implementation. Big

resistance from the workers and management is the main reason that it is still incomplete. Remedy

for this problem is visit to organizations like Pakistan Tobacco Company that very successfully

implemented this technique a decade ago. ‘Seeing is believing’ methodology can be used to make


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people believe in this methodology. Proper implementation of these techniques requires a complete

cultural change in the organization which takes at least 1 to 2 years’ time.

For TPgmt, it is essential to hire people of productivity field if complete cultural change

has to be brought about, which requires 2 to 3 years’ time. In productivity department there has to

be four different sections;

a. Productivity Measurement Section

b. Productivity Planning Section

c. Productivity Evaluation Section

d. Productivity Enhancement Section

Theses sections have to work in collaboration to measure, plan, evaluate and enhance

productivity. This methodology needs more hiring of productivity specialist people and giving

them resources to do their job. Phase wise implementation of this department is also possible by

starting from productivity measurement and subsequently going for productivity planning,

evaluation and enhancement.

7.8 TRIZ and Autonomous Development Implementation

TRIZ theory was basically conceptualized and propounded by Genrich Altshuller, a Russian

(1926-1998). He made several discoveries in this area and developed several tools for TRIZ

implementation. The theme of TRIZ consists of two main concepts i.e. Innovation and Creativity.

It is still generally misunderstood around the globe that innovation and creativity are not possible

in the paradigm of routine daily production operations especially in the manufacturing industry.

ReVelle [121] discussed this aspect in detail and included TRIZ as one of the latest manufacturing

technique for the industry. Based on the arguments of this author, it is believed by this researcher

that though strictly following the routine daily productions and operations rules/procedures can

give results, but in order to get drastic improvements one has to adopt TRIZ tools and techniques


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in the industry. For innovation and creativity, the first and foremost aspect is giving empowerment

to the workers so that they can think and try to improve every step of manufacturing with their

vast experience and tacit knowledge. Knowledge base is the core theme of agile manufacturing as

well as TRIZ. The two basic tools of TRIZ are classical TRIZ tools and ITRIZ [121]. Classical

TRIZ tools are knowledge based tools and are the easiest to be implemented in any organization.

However, for ITRIZ detailed training and understanding of the latest software is essential. In any

organization, it is much easier to start with classical tools which can then be augmented with ITRIZ

software at a later stage. In this organization also, the classical tools were applied. The basis of the

application was giving authority, powers and liberty to think and apply the tacit knowledge to the

employees. This empowerment helped in KAIZEN activities and implementation of 5S techniques

as well. All the workers, line heads, foremen and shop floor engineers were given the liberty to

think and act to improve any aspect of the production/operations and general daily activities. This

technique helped in attaining 1000 Kaizen’s within one year.

Another methodology used for enhancing the innovation and creativity attitude of the

employees was conceptualizing and implementation of the Autonomous Development concept. As

explained earlier, it was realized that considering the high number of demands of the customers,

one or two independent R&D sections cannot fulfill the requirements of development tasks.

Therefore, a complete independent entity was added into every production section. These entities

were in-house small development sections of these production sections. Only two to three basic

machines like conventional lathe, milling machine and grinders were given to these sections. The

team of these sections comprised of two to three expert machinists who worked under the

supervision of the foreman and operations engineers of these production sections. These small

autonomous units were made responsible to develop all the components similar to the one already


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being produced by them. For example, flywheel section was made responsible to develop every

new flywheel (for every new order received) along with complete process, gauges, fixtures and

checking fixtures for the specific product. Similarly other departments were given the tasks related

to their area. This practice actually resulted in inculcating the new concept of concurrent

engineering. There were times that 10 new products were ordered by the OEMs and all of them

were developed in a short span of four months. This was all made possible because all these

autonomous development sections were simultaneously developing their respective components.

In a span of ten months, a record development of 32 components was completed successfully.

These all achievements were made possible because of the empowerment given to these small

units and implementation of TRIZ techniques. Implementation of these concepts require 4 to 5

years.

A new terminology has been introduced in this productivity enhancement model and that is

Autonomous Development (AD). Development is one of the most prominent factors for

organizational success. Only the accurately developed processes can give better productivity with

quality outputs. This is the main reason that development techniques are considered to be most

time consuming and require heavy financial consumption. In most of the world class organizations

like GM, Toyota, Ford, BMW, Mercedes Benz, the Research and Development (R&D)

departments/sections are considered to be the most important assets of the organization. The

mostly misunderstood concept about R&D in Pakistan specifically and in the world generally is

that they develop new products. Actually these departments develop processes which produce

quality products with maximum productivity. The responsibility of these departments is not only

to develop new processes for new products but they also continuously work and redesign and

improve the existing processes of in-production components to improvement of quality and


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productivity. This concept has to be incorporated in Pakistani organizations also. Secondly, the

most important aspect in development of a new product (meaning thereby, development of a

process which can produce the desired product) is the concept of Time to Market. In traditional

manufacturing, developing a new product successfully was considered a mega achievement while

ignoring long development spans at times. In the new millennium however, globalization has

changed several manufacturing concepts. Now successfully developing a process or product in

long span of time is considered a failure. Organizations have to meet the market demand in

minimum possible time to remain competitive. In order to win orders, time to market has to be

shortest possible now a days, otherwise some other organization having reduced time to market

takes away the sales. Similarly, time to market concept should be given due consideration for

improvement of an existing process by improving or redesigning for improvement with minimum

possible time to achieve better productivity and attain competitive advantage. Considering these

challenges, organizations around the globe have been concentrating upon increasing their R & D

capabilities in one way or another. Some have increased the size of their R &D sections in number

of machines or labor. Some have also established more than one R &D sections. Still, the customer

demands are not met in several cases. In the recent past, most of the organizations have started

outsourcing their development activities. A large number of development organizations have

emerged which provide development services to the manufacturing units. This activity is proving

to be expensive.

This concept has been introduced in this research considering all these issues. Its

implementation does not require new hiring. Empowerment has to be given to the sections in which

teams of development can be made. Head of the team should be department/section engineer with

foreman as being his assistant. Two machinists and a designer have to be added in the section and


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these small teams can develop all the parts pertaining to the respective section. In this way with

very minimum possible investment complete concept of Autonomous Development can be

incorporated in a time period of six months.

7.9 Energy Audits

The issue of power crises was discussed by nearly all the respondents. The prevailing energy

crises in Pakistan have affected the overall industry very severely. The problem with generators is

that the manufacturing cost of the product goes very high as per unit cost is high on diesel

generators. This problem has resulted in huge production losses to the industry in general and auto

industry in particular. Factory owners have also started working towards alternate power sources.

The biggest gap found in all this process is the fact that industry people are not focusing on energy

audit of their firms in order to at least reduce their energy requirements. Hence energy audit of this

company was conducted with the help of engineers from the universities. Instead of paying huge

amount of money to the consultants, industry can have Knowledge Transfer Partnership (KTP)

with the academia which will result in benefits to both sides. But these fresh engineers or

engineering students have to be managed by an experienced engineer to make this exercise fruitful.

This was the methodology used in this study which gave fruitful results.

Chapter Summary

The proposed productivity enhancement framework was implemented in a functional

organization. This implementation was done to prove the validity of the model. Implementation

was done stage wise as it requires complete cultural change of the organization. The problems

faced in implementation of this model were noted and suggestions were also documented. This

implementation methodology was written in order to guide the user of this model in smooth

implementation of the suggested techniques. First of all step by step methodology of hiring

educated manpower and their proper placement and future growth was suggested as there is very

less number of educated manpower working on the production lines. Methodology of human


151

resource development was also described. The best solution for implementation of these

techniques is capacity building of the existing manpower. Modified JIT concept which can be

easily followed by all others along with optimization techniques has also been elaborated. Detailed

illustrations of the old layouts have been given showing the gaps and wastages due to poor

planning. The new implemented layout with additional benefit has also been shown. Concept of

agile manufacturing in combination with lean manufacturing has also been discussed. Results and

methodology of activity based costing has also been deliberated upon with the help of case study

of one of the component. Methodologies of implementing TRIZ, TQM, TPM, TPgmt, TPM and

conducting energy audits have also been explained.

Chapter 8- Validation of Model and Discussions

152

CHAPTER 8

VALIDATION OF PRODUCTIVITY ENHANCEMENT MODEL

AND DISCUSSION OF THE OUTCOMES

Implementation methodologies as discussed and explained in the previous chapter are the

guidelines for successful utilization of this productivity enhancement model. It cannot be claimed

that 100% implementation of this model was done, but most of the concepts and techniques

elaborated have been implemented successfully. Radical changes were achieved in a considerably

short span of time despite partial implementation of this model. Owing to certain reasons explained

in the previous chapter, some aspects of this model were not fully implemented. However, this

gives a chance for future research implementation and further confirmation of the model in similar

as well as in different settings, for further refinement of this model. In this chapter the validation

of this model will be proved by highlighting and indicating the improvements achieved due to its

implementation. The improvements achieved and the outcomes of these implementations will be

elaborated in six different paradigms.

1. Improvements achieved in the production volumes

2. Human Resource savings

3. KAIZEN’s achieved

4. Development projects successfully completed

5. Energy audit results

6. Results in financial terms of the outcomes of these implementations


153

8.1 Production Graphs

The production graphs shown in this section start from January 2010 and expand till March

2012. Development of this model started in November 2010. As the stage wise implementation of

this model progressed, the production graphs also showed radical changes. March 2012 was the

time span where maximum optimization of the equipment and the manpower was achieved. After

that more concentration was given to the quality graphs. Before looking at the graphs and

discussing the results, it is pertinent to mention here that all these production targets were achieved

without adding huge number of machines/equipment in the already held assets of the company.

Rather, several machines not required and found extra were removed from the production line and

placed in stores for future utilization. Another aspect to mention is the fact that all these production

volumes were achieved with 10% to 50% reduction in manpower. The energy consumption, which

was a direct cost to the production, was also reduced to 25%- 30%. These figures show under

capacity utilization of the assets of this organization.

Figure 8.1 shows per month production volumes of brake disc from January 2010 to March

2012. All these volumes only include the good pieces as rejections and rework were not included

in these production numbers. The output of 1170 pcs in Jan 2011 hiked to 4630 pcs per month i.e.

396% increase in the production from the same machines with less manpower and less energy

consumption. Figure 8.2 shows the production volumes of Brake Drum. From volumes of 2160

pcs per month, maximum production achieved was 6574 pcs per month i.e. 304% increase in

production. An important aspect to note from these graphs is the fact that there is some fluctuation

in productions owing to fluctuation in supply demands.


154

Figure 8.1 Production Graphs of Brake Disc from Jan 2010 to Mar 2012 showing 396%

Production Increase on Same Machines and Lesser Manpower

Figure 8.2 Production Graphs of Brake Drum from Jan 2010 To Mar 2012 showing a

Production Increase of 304% on Same Machines with Lesser Manpower

400 350 400 350 450704

1184944

782

1234

792

1086117011961112

19701790

1496

1928

1284

4524

3200

28822762

4630

1228

3116

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

`Jan-2010

`Feb-2010

`Mar-2010

Àpr-2010

`May-2010

`Jun-2010

`Jul-2010

Àug-2010

`Sep-2010

Òct-2010

`Nov-2010

`Dec-2010

`Jan-2011

`Feb-2011

`Mar-2011

Àpr-2011

`May-2011

`Jun-2011

`Jul-2011

Àug-2011

`Sep-2011

Òct-2011

`Nov-2011

`Dec-2011

`Jan-2012

`Feb-2012

`Mar-2012

DISC. FRONT BRAKE

11701080135013501260

1620

2070

16201620

2250

1710

2160

2880

1530

3420

2570

16682028

4008

1980

4506

2262

4274

6574

45504890

3870

0

1000

2000

3000

4000

5000

6000

7000

`Jan-2010

`Feb-2010

`Mar-2010

Àpr-2010

`May-2010

`Jun-2010

`Jul-2010

Àug-2010

`Sep-2010

Òct-2010

`Nov-2010

`Dec-2010

`Jan-2011

`Feb-2011

`Mar-2011

Àpr-2011

`May-2011

`Jun-2011

`Jul-2011

Àug-2011

`Sep-2011

Òct-2011

`Nov-2011

`Dec-2011

`Jan-2012

`Feb-2012

`Mar-2012

DRUM FRONT BRAKE


155

In the past, there were months when supply targets were not met due to more demand than

the number of parts produced owing to which complaints of short supplies were received from the

customers. In order to resolve this issue, production was increased on the same machines. Then a

new situation arose where there were months when OEM reduced their production due to certain

issues. In these months it was not possible for the vendors to go on full production as it could result

in huge piles of finished goods which are not financially feasible for any vendor. Normal practice

followed in this scenario is that overtime of the labor is stopped and these CNCs remain stopped

for hours and hours. Considering this situation, the months when less orders were received, the

production on these machines was done on full pace without any stoppage and orders were

completed within a few days’ time. The remaining days in the month when the machines were free

were utilized for development of new parts. That is one strategy which allowed successful

implementation of autonomous development concept. For this practice, the number of parts

produced per hour was calculated and production planning was done in such a manner that

maximum time of the machines was made available for production of other parts or development

of new parts. Quick change-over time of complete production lines including fixtures and tooling

was done to make all these things possible. This resulted in flexible manufacturing lines as several

different types of parts are being produced in this organization.

Similarly, huge production enhancements were achieved for brake drum and exhaust

manifold as shown in Figure 8.3 and Figure 8.4 respectively. These production enhancements were

done on same machines with lesser labor resulting in productivity enhancement. Brake drum

improved from 1300 pcs per month in January 2011 to 4870 pcs per month in Dec 2012. 374%

increase in the production. Exhaust manifold production improved from 1700 pcs per month in


156

Figure 8.3 Production Graph of Brake Drum from Jan 2010 to Mar 2012 showing a

Production Increase of 374% on same Machines with Lesser Manpower

Figure 8.4 Production Graph of Brake Drum from Jan 2010 to Mar 2012 showing a

Production Increase of 199% on same Machines with Lesser Manpower

500 600800

600 600900

130010001100

1500

1000130014001300

2300

1744

11881254

3510

1536

3744

31862970

4870

2640

1200

3024

0

1000

2000

3000

4000

5000

6000

`Jan-2010

`Feb-2010

`Mar-2010

Àpr-2010

`May-2010

`Jun-2010

`Jul-2010

Àug-2010

`Sep-2010

Òct-2010

`Nov-2010

`Dec-2010

`Jan-2011

`Feb-2011

`Mar-2011

Àpr-2011

`May-2011

`Jun-2011

`Jul-2011

Àug-2011

`Sep-2011

Òct-2011

`Nov-2011

`Dec-2011

`Jan-2012

`Feb-2012

`Mar-2012

DRUM REAR BRAKE

200

488600 600

500

900

1300

950

13501450

1700

1400

1800

1350

18001900

704

1550

19041912

3392

2578

1770

2140

2778

1172

3150

0

500

1000

1500

2000

2500

3000

3500

4000

`Jan-2010

`Feb-2010

`Mar-2010

Àpr-2010

`May-2010

`Jun-2010

`Jul-2010

Àug-2010

`Sep-2010

Òct-2010

`Nov-2010

`Dec-2010

`Jan-2011

`Feb-2011

`Mar-2011

Àpr-2011

`May-2011

`Jun-2011

`Jul-2011

Àug-2011

`Sep-2011

Òct-2011

`Nov-2011

`Dec-2011

`Jan-2012

`Feb-2012

`Mar-2012

EXHAUST MANIFOLD


157

November 2010 to 3392 pcs per month in September 2011. 199% increase in production.

Apart from the production improvement achieved on Suzuki parts, similar success was

achieved on Massey Ferguson and Fiat Tractor parts. Valve chamber is a component of tractor

hydraulic pump and huge production enhancements were achieved for this part as well, using some

extra techniques. OEM of Hydraulic pump is MEL which was not able to achieve its production

targets since long, as no vendor was able to manufacture and supply requisite number of value

chambers for them to carry out their production. The supply orders received by MEL in 2010 were

“supply as many as you can produce”. Within a time span of one year, production of this

component was increased from 1053 pcs per month in Dec 2010 to 6870 pcs per month in June

2012 as shown in Figure 8.5, an increase of 652% in production. This was the highest production

target enhancement per month achieved in this organization. In this production increase however,

some extra techniques were also incorporated which included the earlier explained terminology of

“some automation”. Previously the only attempts made were production on CNC machines only

as this is a very highly precision part. So the only strategy used by the top management was

increase in the number of CNC machines in this line. Gradually several operations were brought

out of the CNC and were done on conventional machines. Conventional machines are less

expensive machines and with very less investment several machines can be added. This practice

resulted in huge production increase without increasing the number of CNCs and resultantly, huge

production gains were achieved with very less financial effect.


158

Figure 8.5 Production Graph of Valve Chamber from Jan 2010 to Mar 2012 Showing a

Production Increase of 652% with very Less Financial Investment

468604

950

1200

780630

1200

1478

956

1076

690

1053

12791926

2070

2501

31223210

4035

3392

2997

5087

2000

350

2514

3716

5864

0

1000

2000

3000

4000

5000

6000

7000

`Jan-2010

`Feb-2010

`Mar-2010

Àpr-2010

`May-2010

`Jun-2010

`Jul-2010

Àug-2010

`Sep-2010

Òct-2010

`Nov-2010

`Dec-2010

`Jan-2011

`Feb-2011

`Mar-2011

Àpr-2011

`May-2011

`Jun-2011

`Jul-2011

Àug-2011

`Sep-2011

Òct-2011

`Nov-2011

`Dec-2011

`Jan-2012

`Feb-2012

`Mar-2012

VALVE CHAMBER


159

8.2 Human Resource Savings

Most of the organizations in the world are using one basic technique to enhance productivity,

and that is downsizing. However, it not only creates panic in the employees but also badly affect

the overall performance of the organization because job insecurity fear hamper the performance

of the employees. According to the author of this research, “Downsizing” is the worst method to

be used while “Rightsizing” is the best method. Rightsizing means placing exact number of

employees for the requisite job. If an operation requires 15 people, than exactly 15 individuals

must be placed. A lot of estimations are required for this “exact” estimation. Proper process

analysis with proper layouts and all the techniques discussed in the last chapter have to be

incorporated to make the right estimate. Once proper estimation is done, extra manpower can be

moved to some other operations or can be laid off without having fears of panic in the employees.

The worst practice is that industrialists just start to lay off people without making proper

estimations, a practice that needs to be curbed.

Proper time and motion study and detailed analysis were done in this organization and

“Rightsizing” was done. The results of this rightsizing showed presence of large number of extra

employees. The figures in Table 8.l and graphs shown in Figure 8.6 depict the improvement

achieved in last three years. The numbers of employees have been reduced from an average of 650

per month to only 350 per month. Total pay distributed in 2010 was Rs 65,514,421, pay distributed

in 2011 was Rs 64,180,140 and pay distributed in 2012 was Rs 58,263,169. An important aspect

to be considered is that total number of employees were decreasing in this period and every year

an increment of 15% to 35% was given to the employees. Even then, the total payments made by

the company was on the decrease. While reducing the manpower, the production graphs also show

how much production was also increased resulting in high productivity gains.


160

Table 8.1 Detail of Salary and Employees from Jan-2010 to Dec-2012

2010 2011 2012

Months Gross Salary Total Employees

Gross Salary

Total Employees

Gross Salary

Total Employees

January 6135654 678 5838676 517

4092942 396

February 5903899 635 6324301 546

4803338 329

March 5379678 594 5920840 549

5171223 432

April 5459049 584 5390267 529

5384739 463

May 5605906 578 5090788 490

5347761 429

June 5418625 534 5622988 512

5251830 446

July 5610013 550 5112939 503

5544003 459

August 5882808 498 3988122 422

4745017 454

September 4652362 423 4584036 353

4023192 389

October 5239886 443 6809150 328

4792242 434

November 4935583 437 4428990 365

4626818 384

December 5291399 454 5069043 441

4480064 372

Total 65,514,421 6,316 64,180,140 5,553 58,263,169 4,845

Figure 8.6 Graphs of Three Years Lines showing Number of Employees per Month

0

100

200

300

400

500

600

700

800

2010

2011

2012


161

8.3 KAIZEN’s Achieved

A complete Kaizen culture was developed in the organization. Initially, this philosophy was

implemented on the shop floor as the results are more easily checked and measured, and then this

culture was taken across the board to all the sections and functions of the organization. The first

thing implemented on the shop floor was that the workers were empowered to make any small

change in the daily routine activities. Small financial benefits were added with every incremental

change made or suggested. This incentive boosted the activity and every individual of the

organization started participating in this daily activity. Small improvements were recorded on daily

basis and photographed for record. Even the minutest changes like cleaning the workplace

environment was also encouraged and appreciated, which led to easy implementation of 5S. These

incremental changes were shifted towards the daily operations and functions. Improvement of jigs

and fixtures, improvement of checking fixtures, improvement of gauges, calibration and

persistence use of gauges, improvement of tools and inserts consumption, optimum utilization of

materials and lot more activities similar to these led to 1000 Kaizen’s achieved in one year’s time.

First 200 Kaizen’s out of these are shown in Table 8.2. The result of these improvements have

already been discussed which include: better productivity, better quality of products and processes,

and better profit margins for the organization. These results depict that implementing this

philosophy requires minimum financial inputs but it can provide huge gains for any manufacturing

or services company in the developing countries.


162

Table 8.2 KAIZEN’s In One Year


163


164


165


166


167


168


169

8.4 Development Projects

The Autonomous Development (AD) concept as explained earlier resulted in a system that

is mature enough to give new developments within a very short span of time, which can be huge

in output numbers due to utilization of concurrent engineering concept. Thus, within a short time

span of 10 months, 32 new components were developed along with their complete processes and

gauges. Table 8.1 shows the details of these parts. All the customers for which these parts were

developed showed their complete satisfaction of the methodology and short time to market. All

tiers of Pakistan Suzuki management visited and witnessed the results and gave great appreciation.

Visitors from SMC Japan Head Office also appreciated the new methodology. This new concept

was appreciated for its ingenuity. It was confirmed from the records of Pak Suzuki, Millat Tractors

and also Engineering Development Board of Pakistan that no such precedence exists in the history

that this many parts were development in this short span of time. This organization has received a

lot of new orders on the basis that now they have the capability to develop new products in a very

short span of time.


170

Table 8.3 Parts Developed in a Short Span of Ten Months Due to Autonomous

Development Implementation


171


172


173

8.5 Energy Audit Results

A detailed survey of the company was carried out and it was found that there were a number

of areas which needed immediate improvement. These areas included power losses due to wrong

type of wirings, using over-power motors on the machines, extra lights, use of high power bulbs

instead of energy savers, extra ACs, lose connections etc. In order to keep the project manageable

within time and available resources, the scope of the project was limited to use of power motors

and that too on small scale. First of all, the motors used in one of the section of foundry were

calculated for their power capacity and power usage. Table 8.3 shows the list of these motors and

the cost effect of their power consumption. It was observed that very high power motors were

installed on these machines. Reason for this is that generally machines installed in this organization

are very old and old engineering technique of using high power motors were used in their design.

Same is the case with most of the organizations in automotive parts manufacturers and assemblers

in Pakistan auto industry. In view of this, it was planned to replace the high power motors of 7 Hp

and 20 Hp with lower power motors of 5 HP with alteration of gear box synchronization. Seven

motors were selected as shown in Table 8.4 and their replacement cost was calculated.

Replacement resulted in huge energy and cost savings as shown in Figure 8.7, Figure 8.8 and

Figure 8.9. Figure 8.7 also shows the comparison of power required before the project and after

the project while indicating the actual powered required for the operation. Figure 8.8 shows cost

savings of Rs 0.5 million due to this project, after replacement of only 7 motors. If similar practice

can be performed on all 1130 motors of the factory, the price effect in monetary terms can be easily

imagined. Similarly in Figure 8.9 power saving is shown. After carrying out the energy audit,

actual power generation requirement should be calculated and then new generators should be

bought accordingly.


174

Table 8.4 List of Motors used on One Section with their Cost Effect

Sr.

No.

Motor Location Motor

Size

( HP)

Avg.Current

(Amps)

Avg.Input

Power

( KWH)

Avg.Annual

Energy Use

(KWH)

Avg.Annual

Energy Cost

Rs/Yr

01 Knock-Out 02 2.2 1.42 7668 126522

02 Knock-Out 02 2.2 1.42 7668 126522

03 Magnet on BC-

1

1.5 02 1.29 6966 11

49

39

04 Belt Conveyor -

1 (BC-1)

02 1.2 0.776 4190.4 69141.6

05 Bucket

Elevator -01

03 3.3 2.13 11502 189783

06 Sand Cooler 10 8.5 5.5 29700 490050

07 Blower (Near

Elevator-01)

7.5 04 2.6 14040 231660

08 Belt Conveyor-

02 (BC-2)

02 3.3 2.13 11502 189783

09 Feeder Belt 7.5 07 4.53 14949 246659

10 Bucket

Elevator-02

03 04 2.6 10140 167310

11 Batch Hopper 02 1.5 0.97 218.25 3601

12 Discharge gate

of sand

02 1.5 0.97 109.125 1800.56

13 Rotor Motor 60 95 61.45 239655 3954307.5

14 Carousel Motor 25 35 22.64 88296 1456884

15 Oil pump 0.5 0.4 0.26 1014 16731

16 Water Pump 02 2.2 1.42 5538 91377

17 BC-03[Below

sand mixer]

7.5 4.6 2.98 12516 206514

18 BC-3 (Inclined) 7.5 05 3.23 13566 223839

20 BC-3 (Above

molding

presses)

10 7.5 4.85 20370 336105

TOTAL 157 190.4 123.16 499607.8 8,243,528.66


175

Table 8.5 Replacement of Motors with Cost Effect

Motor Location Motor Size (HP) Replacement Cost (Rs) Total

Replacement

Cost (Rs)

Foundry Existing Replacement Motor Cost Gear box

Cost

BC-03[Below

sand mixer]

7.5 5 11000 32000 43000

BC-3 (Inclined) 7.5 5 11000 32000 43000

BC-3 (Above

molding

presses)

10 7.5 Available

(15500)

32000 47500

Molasses

Muller(Near

750 Kg

Furnace)

20 7.5 Available

(15500)

32000 32000

Fan Motor

Shot Blast

Machine(Small)

30 25 Ok -----

Blower Motor

Shot Blast

Machine(Small)

7.5 5 Ok -----

Sodium Silicate

+ Silica Sand

Mixer Machine

Motor

7.5 5 Ok ------


176

Unit of Power = Horsepower = HP (Along Vertical Axis)

Where,

M-1 = Molasses Muller (Near Induction Furnace 750 kg)

M-2 = BC-03 (Below Sand Mixer)

M-3 = BC-03(Inclined)

M-4 = BC-03 (Above Molding Presses)

M-5 = Sodium Silicate + Silica Sand Mixing Machine

M-6 = Shot Blast Machine (Small) Fan’s Motor

M-7 = Shot Blast Machine (Small) Blower

Figure 8.7 Comparison of Energy Consumption before and after the Project with

Indication of Actual Power Required in Green Color

0

5

10

15

20

25

30

M-1 M-2 M-3 M-4 M-5 M-6 M-7

Motor's Power Before Project

Motor's Power After Project

Max. Power Required


177

Figure 8.8 Financial Effect of Energy Consumption before and after the Project and

Price Saving

Figure 8.9 Power Consumption Difference before and after Project and Power Saving

150,030.2

116,917

33113.2

KWH/Yr

Total Avg.Annual Energy Use byoversized Motors beforeReplacements (KWH/Yr)

Total Avg.Annual Energy Use byMotors after Replacements withproperly sized Motors (KWH/Yr)

Total Avg.Annual Energy Savingsafter Replacement of properlysized Motors (KWH/Yr)

2,475,498.5

1,929,142.7

546,355.82

Energy Cost (Rs/Yr)

Total Avg.Annual Cost of OversizedMotors before Replacements (Rs/Yr)

Total Avg.Annual Energy Cost afterReplacement of Oversized MotorsWith Properly Sized Motors (Rs/Yr)Total Avg.Annual Energy CostSavings (Rs/Yr)


178

8.6 Results in Financial Terms

All these increments resulted in huge financial impacts. In view of the privacy and secrecy

policies of the concerned company, only the revenue differences will be elaborated upon and its

profit margins will not be discussed here. Only 9 parts out of 58 will be discussed here. Table 8.6

shows difference of production in number of parts produced and also the financial affects. In the

first segment of the table, difference in production between 2010 and 2011 is shown. In the

columns difference per month is shown and then its financial effect is calculated. In the last

columns difference per annum and its price impact is depicted. As can be seen from the table, a

huge increase of 18440 drums per annum were achieved for brake drum ST, while an increase of

17902 were achieved for brake drum SB. A total of 50.906 MN Rs were achieved from 2010 to

2011 in total for 9 selected parts. Then in the second row, difference of 2011 and 2012 are shown

giving an increase of 101.617 MN Rs. In the last rows the comparison of 2010 with 2012 is given

showing the difference in two years’ time. An increase of 31670 drums per annum is one of the

most prominent figures. Similarly increase of 23 thousand drum SB and 22 thousand Brake Disc

SBs was achieved in these two years. Overall impact of Rs 143.935 MN was achieved due to

proper implementation of most of the concepts discussed in the model.

Activity cost chains were another achievement tool due to which huge price revisions were

received from the OEMs. These activity cost chains ensured the OEMs about the actual cost of

manufacturing so that they were no longer reluctant to allow the price revisions. Previously, a lot

of price revision requests used to be denied as people were not able to convince the representatives

of the OEMs. All the revision cases which were successfully executed were accumulated. In these

calculations all the revision cases were collected with the effective date since when these revisions

were effective.


179

Table 8.6 Difference in Revenues from 2010 to 2012 after Implementation of the Model


180

Calculations are done for all the parts which have been supplied after these price

revisions and their price impacts. In the columns, first the old price of the component was entered

then its revised price was entered. In the next column, dispatch quantity was written. Then

differences in the prices were totaled in the end. For Suzuki components an extra amount of Rs

172.180 MN was collected for the same number of parts in less than two years’ time. For Al ghazi

tractors a total of 12.890 MN was collected in less than a years’ time. For Millat tractors a total of

Rs 26.984 MN were received in less than ten months’ time. On the whole a total of Rs 217.546

MN was received by the organization as extra amount due to these price revision cases.

8.7 Conclusions & Recommendations

There is no single methodology available in the world which can give a perfect solution to

the industries of the world. There are many techniques and technologies invented which have to

be used in combination for achieving efficiency and higher productivity that can ultimately lead

to better performance and profits. The confusion of management on choosing appropriate

methodology has led to invention of different combinations for different industries. Mostly all

management technologies require a major portion of resources. Several research works have been

initiated all over the world to develop customized solutions for different industries. This research

was an endeavor to establish a comprehensive framework for productivity enhancement in

Pakistan automotive industry. During the course of development of this framework, one of the

most important aspect considered was the types of technologies. According to Sumanth [4], there

are four types of technologies, product technology, process technology, information technology

and managerial technology. According to this author, process technology is most crucial for

productivity enhancement in any organization. However, in this research all four types have been

considered for productivity enhancement because role of other three types in productivity


181

enhancement cannot be ruled out. For managerial technology, the concepts included in the

proposed and validated productivity enhancement model are HRD, Modified JIT, TQM, Agile

manufacturing, SCM, TPM, Tpgmt, Energy Audits, and TRIZ. For process technologies concepts

of process analysis, optimization techniques, modified JIT, Agile Manufacturing, and TRIZ

concepts have been incorporated. For amalgamation of information technologies concepts of ERP,

SCM and CAD/CAM have been included. For integration of product technologies concepts of

Autonomous Development and TRIZ have been incorporated.

In an attempt to provide solution to the industry, different successful models have been

proposed and tested. TAM and TAM2 [91] were attempts in this regard. The biggest shortfall of

TAM however, was that it was established for information technology only. Technology

acceptance model is required for all the three remaining technologies as well, i.e. process

technology, product technology and management technology. The model developed and validated

in this research is actually a TAM covering all four aspects of technology. In an attempt to develop

a model for automotive industry of Pakistan, actually a TAM has been developed and tested which

can be generalized not only to other industries but can also be generalized for all developing

countries.

After establishment of this framework proper implementation methodology has also been

narrated. Using and properly implanting this model will result in higher gains for any industry with

minimum possible investments. In finalization of this model, the first and foremost aspect that was

given most importance was using less capital intensive technologies. However, implementation

has to be stage wise, as implementation stage requires cultural change and resistance in the system

and people make the task even more challenging. This research has shown that the biggest waste

in Pakistan automotive industry is underutilization of capacity. Optimization techniques discussed


182

in this model will result in elimination of these wastes and will result in better productivity. It has

also been understood from this study that similar kind of research has to be conducted on mega

scale if we want to take our industries to the highest ranks in global competition. The sub model

developed in understanding of the industry gave the true picture of the prevailing condition of the

industry and also about the future plans of the top management people of the industry. But once

these models were cross checked and analyzed, it was found that there is huge gap between the

prevailing practices in the industry, the problems faced in the industry, opinion on what should be

the productivity enhancement model of this industry and especially, the future plans of these

experts. For example the problem of resistance by the people, non-availability of skilled

manpower, less educated work force and vendor in-capabilities were highlighted as the core issues

in implementation of latest techniques and technologies resulting in slag in the improvement

activities. But very strangely it was found that in the future plans of these same individuals, there

are no remedial actions against these sore issues. It is believed by the researcher that the core issue

making hindrances in the productivity improvement must be dealt with at top priority. Therefore,

all these remedies have been included in the proposed productivity enhancement framework of

this research.

Detailed recommendations and phase wise implementation methodology has already been

elaborated upon in Chapter 7. Salient points of the recommendations are enumerated as under for

cost effective manufacturing:-

1. Downsizing is not the best option for any organization, as it leads to several issues

including dissatisfaction of employees and intentions to leave. Best option is to conduct

a detailed work study as suggested and “Right Sizing” should be resorted to. During

right sizing it is easy for management to justify the manpower required for a specific


183

task and extra manpower can easily be adjusted in the other sections of the same

company where the need arises. The same skilled manpower can also be employed on

other lines where new lines for new developed parts are to be set up instead of hiring

new and raw workforce.

2. Considering the ever growing demand of the local as well as international market, it is

eminent that one or two R&D sections cannot meet the demands. Several “Autonomous

Development Sections” in the organization can do wonders and time to market can be

reduced drastically. This will ensure enhanced confidence of the customers in the

organizational performance.

3. Automation is expensive. A thorough research should be conducted and feasibility

report of the project must be made before going for “BUY” decisions for automation

lines. Better option available to the manufacturing units is “Optimization First”. As

already shown by the results of this research that underutilization of plant is one of the

major issues in these companies, so optimization can enhance productivity of the

organizations without huge investments. However, if the cost of manufacturing can be

reduced by automation than automation should be made considering the financial costs

in view.

4. Wastage is our worst enemy. We have to identify them daily and eliminate them. The

complete record of daily wastage elimination must be kept for complete cultural change

of the organization.

5. Asking for price increase from OEMs especially in developing countries like Pakistan

is a very sour issue, which can result in annoying the customers. The only solution to

the problem is implementing of “Activity Based Costing” and gradually improving the


184

system to “Activity Cost Chains”. Without long difficult meetings changing markets

prices of the material and labor can easily be incorporated in the final price of the

products.

6. Buying generator is not the first step. First conduct detailed energy audits. A lot of

energy is being wasted in the industry. These energy audits will result in huge cost and

energy savings as shown by the results of validated model. These audits will also show

the actual requirement of the power of the generator to be bought resulting is

investment savings.

7. Energy crisis as faced by the industry of Pakistan warrants concentration on all

alternate energy resources available in the market. This aspect is not deliberated upon

much by top management of the companies.

8. Buying more and more machines and equipment, as demanded by the production and

quality departments is not the right decision. Changing and improving existing layouts

with continual process analyses can increase production on the same machines.

9. Huge raw material inventory can be reduced by conducting material optimization

experiments and daily activities to save material. Process once developed does not

mean that material optimization cannot be done by Kaizen activities.

10. The concept of zero-inventories as given in JIT has not been found very successful

specifically in Pakistan auto industry, as reported by several organizations. Modified

JIT with customized solutions has been found more successful. Considering the kind

of parts and assemblies produced some inventory levels have to be maintained to avoid

production interruptions.


185

11. To have big enterprise is not an indicator of success. Developing a “Niche Enterprise”,

which can adjust as per the demands of the market, is the key to success. Being

agile/adaptive as per requirements of the market will only ensure competitive edge in

the prevailing global competition. Developing flexible manufacturing lines which can

produce different kind of parts as per the requirement is one of the best way to achieve

performance excellence.

12. Being knowledge intensive enterprise is better from being capital intensive enterprise.

Financial cost is one of the most expensive costs for manufacturing. Heavy investments

especially in dead capital inventory (buildings and constructions) must be avoided.

Unfortunately in Pakistani organizations huge investments are made in fixed capital

instead of investing in running capital.

13. Striving for full automation cannot result in cost effective manufacturing. Having

islands of automation with combination of conventional machinery as proved via model

validation gives enhanced profits due to most cost effective manufacturing.

14. Productivity department has to be incorporated in the infrastructure of the organization.

Productivity measurement, productivity planning, productivity evaluation and

productivity enhancement sections have to be made and skilled productivity specialist

have to be hired for better productivity.

15. Having huge maintenance departments are overheads on manufacturing costs.

Implement Total Productivity Maintenance concept by enhancing worker skills to

reduce the overheads of the company.

16. SCM department and MM departments cannot work effectively and efficiently without

proper implementation of Supply Chain Management Philosophy. This philosophy has


186

to be implemented right from the organogram of the company. For easy implementation

ERP solutions have proved to be very successful especially in Pakistani organizations.

But every organization has to conduct a comprehensive need assessment analysis

before final investment in any ERP solution. Implementing expensive solutions like

SAP for small and medium organization is not the advisable investment decision.

17. Quality Culture development in any organization is the prime step. Starting from

investing in expensive solutions like Six Sigma before incorporating quality culture in

any organization cannot give desired results. Implementing PDCA circles first is a

better choice. Running after ISO certification only cannot ensure the quality change

required, as is perceived erroneously in Pakistani organizations. Proper utilization of

SPC tools on-ground can ensure better quality controls. Quality Assurance in

combination with quality control departments has to be developed and made effective

for ensuring this quality culture.

18. We have to change the Human Resource Departments into Human Resource

Development Departments to ensure better performance of the employees. Skills of the

employees have to be enhanced through training and career development. Educated

manpower has to be employed with maximum possible efforts to make all the above

points successful. Trying to hire less educated manpower to save labor cost is not a

good choice at all. Job satisfaction and job security of the employees have to be ensured

through the measures as explained in chapter 7 to enhance and ensure better

productivity of the workers and the organization. EOBI and workers old age benefits

are not overheads they actually add value to the product manufactured in the longer

run, these aspects are mostly neglected in these organizations.


187

19. Continuous Improvements through KAIZEN Culture can only make the great change

at the end of the day. Incentive has to be given to the workers to ensure implementation

of this culture

20. TRIZ techniques of “Innovation and Creativity” are essence of success for any

organization of any nature. In daily operations as well these aspect has to be inculcated

which can only come by through empowerment and worker participation. We have to

implement the tools of TRIZ to achieve organizational success.

Chapter Summary

In this chapter the validation of this model has been proved by highlighting and indicating

the improvements achieved due to its implementation. The improvements achieved have been

elaborated in six different paradigms. Improvements achieved in the production volumes,

elaborated with the help of production graphs. Human Resource savings. KAIZEN’s Achieved.

Development projects successfully completed. Energy audit results. Results in financial terms of

the outcomes of these implementations. Production graphs showed enormous increase in the

production volumes i.e. up to 652% production increase in one of the component. All these

production targets were achieved without adding even a single machine/equipment in the already

held assets of the company. Rather, several machines not required and found extra were removed

from the production line and placed in stores for future utilization. Another aspect to mention is

the fact that all these production volumes were achieved with 10% to 50% reduction in the

manpower. The energy consumption which was a direct cost to the production was also reduced

to 25%- 30%. 1000 Kaizen’s were achieved in one year’s span due to implementation of this

model. Due to implementation of Autonomous Development concept several new products were

developed in a record time. In financial terms overall impact of Rs 143.935 MN was achieved in

revenues of the organization due to proper implementation of most of the concepts discussed in

the model. Recommendations have been given in this chapter for all the stake holders.

188

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201

ANNEXURE A

FORMULAE FOR PRODUCTIVITY MEAUREMENT

OUT QUANTITY = Considered as All Finished Cars produced in the respective Year

GROSS OUTPUT PRICE= Total Number of Product produced in each year x Base Period Ex-

Factory Prices + Prices of Partially Produced Products Obtained from (Difference of Work

in Process Inventory at the beginning and End of Financial Year)

(Consider by multiplying through base period Price into the respective different Product of Cars)

VALUE ADDED OUTPUT= Deflated Gross Output – Deflated Material – Deflated Energy –

Deflated Other expenses

(Counted by subtracting Deflated Material, Deflated Energy and Deflated Other expenses from

Gross Output Price)

OUT CAPACITY= Considered as The output Capacity of the Manufacturing Unit obtained from

Notes to Financial Statement

NUMBER OF EMPLOYEES= Obtained from Financial statement

Counted Number of direct Labour of Permanent Employees of the Company for that specific year

Total No of Man Hours in One Year= 48 Hours per Week (Obtained from Labour Policy of

Pakistan) Out of 52 week we have taken 20 Gazette Holidays and 52 Sunday i-e Off week days

become 12 weeks. Subtracting 2 more weeks of Ramzan from total as in Ramzan working hours

counted as half. So Total 12 weeks are taken out from 52 weeks, making them 40 week of work

per year. (48 Hours per week x 40 weeks= 1920 Hours)

LABOUR MAN HOURS = Number of Employees x 1920 Hours per year

(It has been calculated from the Labour Policy of Pakistan, allowable working hours to the No of

employees and with respective working days in a year.)

202

Annexure A

LABOUR VALUE= Salaries Wages and Benefits from Cost of Sales + Salaries Wages and

Benefits of Distribution and Marketing Cost + Salaries Wages and Benefits of Administrative

Expenses (Extracted from Note to Financial statement, mostly given at Point 23, 24 and 25)

DEF LABOUR VALUE= Deflating Labour value with the Bas value price.

FIXED CAPITAL= Noted as of Book Value of Property Plant and Equipment

WORKING CAPITAL= Capital work in Progress

TOTAL CAPITAL= Fixed Capital + Working Capital

DEFLATED TOTAL CAPITAL= By Adding deflated working and Fixed capital.

MATERIAL= Raw Material consumed + Store and Spares consumed)

(Accounted from point 23 of Notes to Financial Statements with heading of Cost of sales while

reducing it to cost of goods manufactured from the same column Raw Material Consumed and

Stores and spare)

ENERGY= Fuel and Power + Fuel and Power of Distribution and Marketing Cost, +

Administrative Expenses on Fuel and Power

(Counted as Fuel and Power from Cost of Sales, Distribution and Marketing Cost, and

Administrative Expenses)

DEFLATED ENERGY= Deflating Energy with the Base Period

OTHER= Cost of Good Manufactured (from Heading of Cost of Sales) + Distribution and

Marketing Cost + Administrative Expenses + Other Operating Expenses + Finance Cost +

Taxation – {(Raw Material Consumed + Stores and Spares Consumed + Salaries Wages and

Benefits + Fuel Power from Cost of Sales) + (Salaries wages and benefits + Fuel and Power from

203

Annexure A

Distribution and Marketing Costs) + (Salaries wages and benefits + Fuel and Power from

Administration Expenses)}

DEFLATED OTHERS

TOTAL INPUT= Deflated values of Labour + Deflated Working Capital + Deflated Fixed capital

+ Deflated Material + Deflated Energy and Other Expenses

Accounted as Deflated values of Labour, Working and Fixed capital, Material, Energy and Other

Expenses

TOTAL PRODUCTIVITY= 𝐺𝑟𝑜𝑠𝑠 𝑂𝑢𝑡𝑝𝑢𝑡

𝑇𝑜𝑡𝑎𝑙 𝐼𝑛𝑝𝑢𝑡𝑠

Extracted by diving Deflated Gross Output with the Total Inputs

PRODUCTIVITY INDEX=

Partial Productivity of Labor= 𝐺𝑟𝑜𝑠𝑠 𝑂𝑢𝑡𝑝𝑢𝑡

𝐿𝑎𝑏𝑜𝑢𝑟 𝑉𝑎𝑙𝑢𝑒

Extracted by Dividing Deflated Gross Output with Deflated Labor Value

Partial Productivity of Material= 𝐷𝑒𝑓𝑙𝑎𝑡𝑒𝑑 𝐺𝑟𝑜𝑠𝑠 𝑂𝑢𝑡𝑝𝑢𝑡

𝐷𝑒𝑓𝑙𝑎𝑡𝑒𝑑 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝑉𝑎𝑙𝑢𝑒

Extracted by Dividing Deflated Gross Output with Deflated Material Input Value

Partial Productivity of Energy= 𝐷𝑒𝑓𝑙𝑎𝑡𝑒𝑑 𝐺𝑟𝑜𝑠𝑠 𝑂𝑢𝑡𝑝𝑢𝑡

𝐷𝑒𝑓𝑙𝑎𝑡𝑒𝑑 𝐸𝑛𝑒𝑟𝑔𝑦 𝑉𝑎𝑙𝑢𝑒

Extracted by Dividing Deflated Gross Output with Deflated Energy Value

Partial Productivity of Capital = 𝐷𝑒𝑓𝑙𝑎𝑡𝑒𝑑 𝐺𝑟𝑜𝑠𝑠 𝑂𝑢𝑡𝑝𝑢𝑡

𝐷𝑒𝑓𝑙𝑎𝑡𝑒𝑑 𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝑉𝑎𝑙𝑢𝑒

Extracted by Dividing Deflated Gross Output with Deflated Total Capital

Total Productivity = 𝑂𝑢𝑡𝑝𝑢𝑡

𝐼L + 𝐼 M + 𝐼 F,C+ 𝐼 W,C + 𝐼 E + 𝐼X

204

ANNEXURE B

PRODUCTIVITY SURVEY

Q 1: How you define productivity?

Q 2: Do you have any productivity measurement, evaluation, planning and improvement

department in your organization?

Q 3: Have you hired any productivity personnel in your organization?

Q 4: How productivity is measured in your organization?

Q 5: What productivity improvement practices have been adopted in your organization?

Q 6: What latest technologies have been adopted in your organization?

Q 7: According to you which are the best suitable technologies for Pakistan Automotive

Industry?

Q 8: What are your experiences in attempts to implement latest technologies in Pakistan

Automotive Industry?

Q 9: What are future plans of your organization for implementing new technologies?

Q 10: According to you how Knowledge Management can be used (especially tacit

knowledge) to enhance productivity in Pakistan Automotive Industry?

Q 11: What are the effects of labour unions of the productivity of the firm?

Derived and Modified from

Linna, P. and Pekkola, S. (2010). Defining and measuring productivity in the public sector: managerial perceptions.

International Journal of Public Sector Management, 23 (5), 479-499.

Thomas, A.J., Barton R. and John E.G. (2008). Advanced manufacturing technology implementation: A review of

benefits and a model for change. International Journal of Productivity and Performance Management, 57 (2), 156-

176.

Sigala, M. and Chalkiti, K. (2007). Improving performance through tacit knowledge externalization and utilization.

International Journal of Productivity and Performance Management, 56 (5/6), 456-483.

Saad, M. and Patel, B. (2006). An investigation of supply chain performance measurement in the Indian automotive

sector. Benchmarking: An International Journal, 13 (1/2), 36-53

Sumanth, D.J. (1998). Total Productivity Management, A systematic and quantitative approach to compete in quality,

price and time. St. Lucie Press, Florida.

205

ANNEXURE C

Improved Layouts of Different Sections

206

Annexure C

207

CURRICULUM VITAE

Name: Sheikh Zahoor Sarwar

Father’s Name: Sheikh Muhammad Sarwar

Regn. No.: F-08-120

Contact: 0321-5564525

Address: House 27A, Park Road F-8/1 Islamabad

Phone: 0512852566

E-mail (s): [email protected]

Courses Passed:

Name Employer Organization: Institute of Space Technology

Name of the Controlling Officer: VC Engr Imran Rehman

Subject Exam Held in Grade GPA 1 Total Productivity

Management

Fa 08 A 4

2 Manufacturing

Technologies

Fa 08 A 4

3 Seminar in Competitiveness

and Technology

Sp 09 A 4

4 Independent Study

(Research)

Sp 09 S 4

5 Industrial Psychology Su 09 A 4 6 Research Methodology Su 09 V 4 7 Professional Ethics Su 09 S 4 8 Finance for Technical

Managers

Fa 09 A 4

9 Quantitative and Qualitative

Methods

Fa 09 A 4

10 Business Communication Sp 10 A 4 11 Research Methodology for

Engineering Managers

Sp 10 A 4

12 Seminar in Technology,

Governance and

Globalization

Sp 10 A 4

13 Technology, International

Trade and Economic

Development

Su 10 A 4

14 Productivity Engineering

and Management

Su 10 A 4

16 Research Proposal

Development Techniques

Su 10 A 4

17 Dissertation Research

(PhD)

Su 10 S 4

208

PUBLICATIONS

Sheikh Zahoor Sarwar and Dr Danial, S. P. (2013). Identifying Productivity Lapses

of Pakistan Automotive SMEs. J. Basic. Appl. Sci. Res., Vol 3, No 12, pp 8-17.

(HEC Recognized Journal). X Category Journal.

Sheikh Zahoor Sarwar, E. Mirza, N. Ehsan, K. Khan and Huma Hanif. (2012).

Determining Impact of Age and LOS on Job Satisfaction: A Case Study of Pakistan

Automotive Industry. International Journal of Human Resource Management, Vol

24, No 2, pp 415-435. DOI:10.1080/09585192.2012.674960 (HEC Recognized

Journal). X Category Journal.

Asad Ilyas, H. Nasir, F. Hussain, M. R. Malik, Zahoor Sarwar. (2013). Evaluating

Business Schools Service Quality using SERVQUAL Model. J. Basic. Appl. Sci.

Res., Vol 3, No 5, pp 710-716. (HEC Recognized Journal). X Category Journal.

Sheikh Zahoor Sarwar et al. (2013). To Study the Rise in Satisfaction Level of

People due to E-Governance Initiative by Government of Punjab-A Case Study of

Excise and Taxation Department. IOSR Journal Of Humanities And Social

Science, Vol 9, No 5, pp 64-70. DOI: 10.9790/0837-0956470 (HEC Recognized

Journal).

Sheikh Zahoor Sarwar et al. (2012). Productivity Analysis of Honda Atlas and

Indus Motors: Automotive manufacturing companies of Pakistan. International

Journal of Productivity and Performance Management, Vol 61, No 2, pp 173-193.

(HEC Recognized Journal).

Hassan Ali, A. A. Khan, D. S. Pirzada, W. Arif and Zahoor Sarwar. (2012).

Technology spillover impacts on total productivity of the manufacturing sector in

209

Pakistan. African Journal of Business Management, Vol. 6, No 9, pp. 3490-3503.

DOI: 10.5897/AJBM11.2352 ISSN 1993-8233. (HEC Recognized Journal).

Abeer Khan, Dr. N. Ehsan, E. Mirza, Sheikh Zahoor Sarwar. (2012). Integration

between Customer Relationship Management (CRM) and Data Warehousing.

Procedia Technology Vol 1, pp 239 – 249.

H. J. Chughtai, N. Ehsan, E. Mirza, Sheikh Zahoor Sarwar (2012). Database

model for traffic routing and planning parameters in commercial Microwave

networks. Procedia Technology, Vol 1, pp 230 – 238.

Sheikh Zahoor Sarwar et al. (May 2010). Barriers of Productivity in Public Sector

Automotive Industry of Paksitan. World Academy of Science, Engineering and

Technology, Issue 41 (pp. 1191-1195). Tokyo, Japan.

Sheikh Zahoor Sarwar et al. (2011). Is there is relationship between JS and OCB:

A case study of Pakistan Telecom sector. Proceedings of World Academy of

Science, Engineering and Technology (August 2011), pp.887-895.

Arshad, K., Rafique, T., Ishaque, A., Sarwar, Z. and Nisar, A. (2011)

“Developing a Suitable Framework for Appropriate Project Management

Application for IT Industry of Pakistan" Proceedings of 14th Toulon Verona

conference on Excellence in Service, ICQSS 2011, 1-3 September 2011, Alicante,

Spain. I.S.B.N : 978 88904327-1-2 (pp. 111-115)

Sheikh Zahoor Sarwar et al. (2010). Noninvasive Imaging System for Visually

Impaired People. Proceedings of 2010 3rd International Conference on Computer

Science and Information Technology, July 9-11, (pp1-6), Chengdu, China. DOI

10.1109/ICCSIT.2010.5564650.

http://dx.doi.org/10.1109/ICCSIT.2010.5564650

http://dx.doi.org/10.1109/ICCSIT.2010.5564650

210

A.Ahmed, S. Ahmed, N.Ehsan, E. Mirza and Sheikh Zahoor Sarwar. (2010). Agile

Software Development: Impact on Productivity and Quality. 5th IEEE Conference

on Management of Innovation and Technology, June 2-5, (pp 287-291), Singapore.

N. Ehsan, S. S. Kakakhel, S. Ashraf, Sheikh Zahoor Sarwar. (2010). Impacts of

Gender Discrimination on the Motivation of Female Employees. Proceedings of

4th International Technology, Education and Development, Conference, INTED,

8-10th March, (pp 1506-1512), Spain. ISBN: 978-84-613-5538-9.

M. W. Bhatti, N. Ehsan, A. Ishaque, F. Hayat, S. A. Phatak, Zahoor Sarwar.

(2010). An Investigation of changing requirements with respect to development

phases of a software project. IEEE International Conference on Computer

Information Systems and Industrial Management Applications October 8-10,

Cracow Poland. DOI:10.1109/CISIM.2010.5643639.

N. Ehsan, G. M. Mir, Zahoor Sarwar, A. Ishaque, E. Mirza, “Manufacturing

Modern Structures: A Drift in Materials and Manufacturing Technologies”,

International Conference on Asia Pacific Business Innovation and Technology

Management, January 24-26, 2010.

ISBN: 978-971-94544-0-3.

N. Ehsan, S.Ahmed, H. Raza, E.Mirza, Zahoor Sarwar, A.Ishaque and A. Akhtar,

“Total Quality through Forecasting and Optimization of Human Resource in Public

Organization”, International Conference on Asia Pacific Business Innovation and

Technology Management, January 24-26, 2010. ISBN: 978-971-94544-0-3.

211

UNDERTAKING

I certify that research work titled “Development of a Productivity Enhancement Model for Private

Sector Automotive Manufacturing Industry of Pakistan” is my own work. The work has not been

presented elsewhere for assessment. Where material has been used from other sources it has been

properly acknowledged/referred.

Sheikh Zahoor Sarwar Registration Number: 10-UET/PhD-CASE-EM-46

212

SUPERVISOR’S COMMENTS

Supervisor Dr Danial Saeed Pirzada Visiting Faculty CASE

department of engineering mangement center for …

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