msc thesis zhida xu
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University of Groningen Faculty of Economics & Business
Master Thesis,
MSc Business Administration, Operations & Supply Chains
Decision making process for Low Cost Country Sourcing based on Total Cost of Ownership: a case study in European plastic pipe and fitting industry
Final Version
First supervisor: Prof. Dr. D.J. Kamann
Second supervisor: Dr. S. Brinkman
28th September, 2009
Zhida Xu
S1546511 [email protected]
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Abstract
This study about Low Cost Country Sourcing (LCCS) intends to answer
two questions: 1) Which countries offer low cost sourcing opportunities?
And 2) Is it attractive to purchase from that country in the medium and
long term? The case study method is used in one European plastic pipe
and fitting manufacture and it addresses the following sub research
themes: product selection for low cost country sourcing, low-cost
country selection based on Total Cost of Ownership principle and
sustainability of the low cost. These issues are integrated into a
decision process model for LCCS. The main finding of the study is that,
among 21 evaluated low-cost countries, India, Indonesia, Egypt, Philippines,
and Tunisia are found to be attractive as destination of LCCS, and their low
cost condition are sustainable in the medium term (3 to 5 years). Vietnam,
Morocco, Turkey, Argentina, Mexico, and Brazil also have the potential. China
is an ideal destination compared with other low-cost countries, but its window
of opportunity as a low-cost country is closing. Some organizational problems
regarding purchasing practice were identified within the case company during
the research process. They are analyzed and recommendations are provided.
The decision process model provides management a “one stop shopping” for
LCCS analysis, and it can be used for repetitive propose.
Key words: Low Cost Country Sourcing, Total Cost of Ownership,
Sustainability of low cost sourcing, Demographic Bonus
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Acknowledgement
I would like to express my appreciation to my thesis supervisors: Prof. Kamann and Dr. Brinkman, for their guidance on theory and methodology throughout this graduation project. I would like to appreciate Mr. Richard van Delden from SMIT for giving me this opportunity to do this graduation project in the company. And I would like to express my special thanks to Mr. Olle Klaasen, my coach in SMIT, for his support and help during this project. I also would like to thank Prof. Marcel Timmer from University of Groningen for his guidance on the topic of international comparison. And I would like to thank Ana Isabel Moreno Monroy, PhD candidate at University of Groningen, for her guidance on labour cost development and industrial agglomeration.
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Table of Contents
1. Introduction ..................................................................................................5
2. Theoretical Framework ................................................................................8
2.1 Defining Low Cost Country Sourcing (LCCS) .........................................8
2.2 Total Cost of Ownership and Low Cost Country Selection criterion........9
2.3 Product selection for Low Cost Country Sourcing.................................12
2.4 Sustainability of the low cost .................................................................15
2.5 LCCS decision process model ..............................................................19
3. The Case ...................................................................................................21
4. Product selection for LCCS........................................................................23
5. Low cost country selection.........................................................................30
6. Sustainability of low cost country sourcing.................................................40
7. Discussion of results ..................................................................................44
7. 1 Discussion of LCCS country selection .................................................44
7.2 Discussion of organization issue...........................................................47
8. Conclusion .................................................................................................51
Reference ......................................................................................................54
Appendix 1 Original score for LCCS country selection ..................................58
Appendix 2 Sensitivity Analysis of country selection models .........................61
Appendix 3 Break-down analysis for each low cost country’s performance...63
Appendix 4 Threshold of assigning scores to demographic bonus study.......68
Appendix 5 Data of dependency ratio development.......................................69
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1. Introduction
International purchasing and outsourcing have become pervasive business
activities for multinational enterprises (MNEs) thanks to the wave of
globalization and the progressive elimination of trade barriers. Given that
multinationals are facing more and more cost pressures, it is a tendency that
MNEs search for resources and reallocate production in countries with low
cost. Research from Aberdeen Group (2005) shows that Low Cost Country
Sourcing (LCCS) is becoming a common strategy, and through 2008 the
average of the total spending for direct materials with low-cost country
suppliers will almost double, from 21% to 39%. Sourcing from low cost
countries can benefit the bottom line and improve companies’
competitiveness. According to a report from IBM Global Business Service
(2006), total savings up to 40% on purchased goods can be realized.
Regarding the motivations of Low Cost Country Sourcing, besides the
advantages of low cost, companies can focus on core business, benchmark
competitors in their outsourcing endeavours, own a broad supply base,
access to better quality and establish a sales footprint for future market entry
(Cater et al, 2005; Andersson et al, 2007). On the other hand, LCCS strategy
also involves lots of risks. Some of the commonly identified risks include
supply disruption, long lead times due to far transportation, security issues
due to political instability in the host country and “hidden cost” such as foreign
exchange control, tariffs, duties and other kind of taxes (Fitzgerald, 2005).
Besides, some indirect risks come from communication difficulty because of
culture difference, insufficient intellectual property protection, spillover effect
of technical know-how and corporate social responsibility issues such as use
of child labor in the low cost countries. Poor quality is also found to be one of
the concerns, which contradicts with previous discussions as an advantage.
This shows that the quality level in low cost countries is not consistent.
In recent years, it is witnessed that some of the low-cost countries are getting
expensive. For example, the labor cost in the areas of Yangtze River Delta
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and Pearl River Delta in China increased significantly since 2006, and some
manufactures even had difficulties to recruit workers (Business Week, 2006).
In addition, due to fluctuation of oil prices, oversea transportation cost also
increased. The question of “is LCCS still viable” emerged.
All of the risks mentioned above give the caution that LCCS need to be
carefully managed. When companies choose to do low cost country sourcing,
it is important to look beyond the direct price paid to suppliers, because there
are lots of “hidden costs”, such as inventory build-up due to long lead time,
machine down time caused by bad quality. Also, activities such as supplier
selection, negotiation, contracting, communication, sample testing, quality
checking are very time consuming. In order to take a comprehensive view to
evaluate cost, the framework of Total Cost of Ownership (TCO) provides
useful guidance. If management does not take a total cost view to do Low
Cost Country Sourcing, it is possible to end up with negative total savings.
There has been lots of intensive discussion about Total Cost of Ownership in
the literature (Ellram, 1993, 1995, 1996; Ellram and Maltz, 1995; Olsen and
Ellram, 1997; Ferrin and Plank, 2002). But limited study applies this view in
the situation of low cost country sourcing. Especially, it is necessary to study
how the low cost countries should be selected. Therefore, the objective of this
paper is to develop a model for LCCS country selection based on Total Cost
of Ownership. Secondly, given that LCCS should be a long term strategy, it is
also important to investigate for how long the low cost sourcing could be
sustainable. The main research questions are:
1) Which countries offer low cost sourcing opportunities? 2) Is it attractive to purchase from that low cost country in the medium and
long term? The way to measure the sustainability of low cost is based on the theory of
Demographic Bonus, which links the age structure transition of a country’s
population to its economic growth. Besides, as a first step to conduct the
research, certain products that are suitable for LCCS must be selected. A set
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of selection criterion are summarized based on current literatures, and a
matrix calculation method is applied by using data from a questionnaire
survey to purchasing managers. Finally, these different steps of evaluation
are integrated into a decision process model. By applying this model,
companies can select the proper product for low cost country sourcing,
identify attractive low-cost countries for those products and assess for how
long can it is beneficial to purchase from that country. This is a generic model
which can be used for repetitive purpose and long term decision making.
The main finding from this study is that, among 21 evaluated low-cost
countries from different areas of the world, India, Indonesia, Egypt, Philippines,
and Tunisia are found to be attractive as destination of LCCS, and their low
cost condition are sustainable in the medium term (3 to 5 years). Vietnam,
Morocco, Turkey, Argentina, Mexico, and Brazil also have the potential. China
is indeed an ideal destination compared with other low-cost country, but it is
losing the low cost attractiveness gradually in the medium term. During
research, certain organizational problems concerning purchasing practice
emerged and they are analyzed and discussed separately.
The General recommendation to management is that it is better to purchase
from big countries (in the respect of territory and scale of economy) because
(1) big countries have relatively abundant resources and (2) the social-
economic development in big countries are normally unbalanced, which
provide more possibilities to prolong the process of cost increase.
The rest of the paper is organized in the following way. Part 2 summarized
current literatures on the different decision areas of low cost country sourcing,
and it concludes with the decision process model. Part 3 introduces the case
company. Part 4 to 6 respectively discuss Product selection for LCCS,
Country selection for LCCS and Sustainable purchasing from low-cost country.
Each part contains its own methodology, data collection and analysis sections.
Part 7 discuss the main findings of this study and the emerged organizational
issues. The paper ends with conclusion and recommendation.
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2. Theoretical Framework
2.1 Defining Low Cost Country Sourcing (LCCS)
Global sourcing, international purchasing and low cost country sourcing, as
names of business practices, are interchangeable for business practitioners.
However, to be rigorous for the research, they should be clearly distinguished,
because these terms do differ from scale and scope. Starting with the term
“sourcing”, according to Kotabe and Murray (2004, page 9), sourcing is used
to describe management the flow of component and finished products in
serving foreign and domestic markets. Global sourcing is a broad term. It is a
discussion of sourcing on a more strategic level. Trent and Monczka (2003)
defines global sourcing as the worldwide integration of engineering,
operations and procurement centres within the upstream portion of a firm’s
supply chain. They also provide a continuum model of different stages of
worldwide sourcing (Table 1), and according to this continuum, international
purchasing, as a general term, belongs to level 2 and 3, while a true global
sourcing practice (level 5) cannot be done only by the purchasing function.
Level 1 Level 2 Level 3 Level 4 Level 5
Engage in
domestic
purchasing
only
Engage in
international
purchasing as
needed
International
purchasing as
part of
sourcing
strategy
Integration and
coordination of
global sourcing
strategies across
worldwide
locations
Integration and
coordination of global
sourcing strategies
with other functional
groups
Table 1. A continuum of different levels of worldwide purchasing practice
(Trent and Monczka, 2003)
When discuss “sourcing” from a contractual point of view, there are “intrafirm
sourcing” which is between subsidiaries, and “outsourcing” which is provided
by outside suppliers. From a location point of view, there are domestic
sourcing and offshore sourcing (Kotabe and Murray, 2004). Sometimes
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outsourcing and offshoring are confused. Based on the classification above,
outsourcing is a make-or-buy decision, while offshoring is outsourcing from a
foreign country. Javalgi, dixit and Scherer (2009) categorized offshoring
business models into: “captive offshoring”, “offshore outsourcing” and
“offshore development centres”. Among these, the strategy behind offshore
outsourcing is to create value though the low cost, most of the time in low-cost
emerging economies such as China and India. This idea is consistent with the
Low Cost Country Sourcing practice.
There are some discussions about Low Cost Country Sourcing in business
literatures (Fitzgerald, 2005; Timmermans,2005; IBM global business services,
2006; Spekman, 2008) and some discussions about China sourcing in
academic literatures (Nassimbeni and Sartor, 2004; Asta, 2005, 2006;
Millington, Eberhardt & Wilkinson, 2006; Bankvall and Fredriksson, 2007), but
there is not a consistent definition for Low Cost Country Sourcing. Based on
literature review, in this study, it is defined as A business practice that
multinationals in developed economies purchase materials, components,
products or services from low-cost emerging economies. It will be
referred as LCCS in the rest of the paper.
2.2 Total Cost of Ownership and Low Cost Country Selection criterion
To assess which low cost country to purchase from on a macro level involves
a lot of considerations. Besides the purchasing price of product from that
country, factors such as the capability of industry sector, product quality and
transportation time/cost are important. This comprehensive way of evaluation
complies with the modern principle of purchasing which is called Total Cost of
Ownership.
Traditionally, the mission of purchasing function is to buy materials,
components or services from outside parties with low prices. Therefore, it is
common that purchasers’ primary concern is the low price. However, with the
development of modern supply chains, purchasing begin to play a strategic
role for the company, and it is important to pay attention to other performance
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objectives besides cost price, such as quality, speed, dependability and
flexibility (Slack and Lewis, 2001), since bad performance on these aspects
will also cost money. Since 1980s’ there has been some development and
evolution of methods to find the “total price” for purchasing. Some contribution
include the concept of Total Cost (Cavinato 1991, 1992), Life cycle costing
(Jackson and Ostrom, 1980), Product life cycle costs ( Shields and Young,
1991) and Total Cost of ownership (Ellram 1993, 1994, 1995). These
concepts are all related and share the same belief that purchasers should not
only focus on the face price, but they should take into account other factors in
the purchasing activities in order to derive the total price. Among those
concepts, Total Cost of Ownership (TCO) has been widely accepted and
Ellram did a serial of contribution in this field.
According to Ellram and Siferd (1993, page 164), Total Cost of Ownership
implies that all costs associated with the acquisition, use and maintenance of
an item be considered in evaluating that item and not just the purchase price.
Ellram (1993) classified the total cost of purchasing into three categories: 1)
Pre-transaction cost, such as investigating and qualifying sources, selecting
and educating suppliers; 2) transaction cost, such as price, order placement,
delivery, tariffs/ duties, billing, inspection and follow-up; 3) Post-transaction
cost, such as failure cost, return and repair costs, etc. It is believed that taking
a TCO perspective not only helps to disclose the “real price” or “hidden cost”
in purchasing activities, and it is also a valuable method to analyze
purchasing process in order to find improvement opportunities.
When applying the Total Cost principle to low cost country sourcing, it is
necessary to consider the following country selection criterion. Firstly, the
level of production cost should be watched. Production cost includes many
components, such as raw material, labour, energy, equipment and land price.
Given that multinationals tend to transfer labour intensive production to low
cost countries, labour cost is taken as a lead indicator. Labour cost has two
components: wage cost is the employee’s “take-home money” and non-wage
cost refers to different kinds of social security and taxes paid by the employer.
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Secondly, competence and quality are important dimensions and they are
related. Competence measures what the industrial sector can do, namely can
the manufacturers in that low cost country only provide assembly service or
they can master state-of-art technology which is driven by strong R&D
capability. Quality measures how good the performance is. However, quality
itself is difficult to measure. Normally it needs to be judged based on real
product, let along measuring the product quality on a country level. Therefore,
the logic here is to exam the quality management system among the
manufactures. ISO certificate is a widely accepted measurement of quality
management system; therefore, percentage of ISO certificate ownership of
manufactures is an acceptable indicator.
Thirdly, the importance of logistics does not need to be over emphasised.
Besides the direct transportation cost and lead time, time to export, such as
time to pass custom sometime can cause delay of responsiveness. The
facility of infrastructure is also need to be checked. For international
purchasing, duty and tariff are important concern, especially the anti-dumping
tariff and safeguard measures. These special tariff could suddenly take away
all the saving potential.
Last but not least, the “Business environment” contains a lot of cost drivers
which are normally hidden from the surface. When product requirement and
specification are disclosed, the spill-over effect of know-how is somewhat
inevitable. Therefore, it is critical to protect purchasing party’s intellectual
property. In some low cost countries, child labour use is common practice and
industrial pollution is serious. This will damage the reputation of the
purchasing party. Finally, the foreign exchange risk sometimes could also
take away all the saving effect on LCCS when there is dramatic exchange
rate fluctuation against the purchaser. To sum up, the above discussion can
be summarized into a country selection model for low cost country sourcing
based on total cost view. These country selection criterions are summarized
in a tree chart in Figure 1.
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Figure 1 Low Cost Country selection criterion
2.3 Product selection for Low Cost Country Sourcing
What kind product is suitable for purchasing from low cost countries is a very
critical issue. Due to different product nature and other contingency factors,
some product can show significant saving potential when buying from the
same low cost country, but some may not, and in some cases, it could end up
with negative savings. Therefore, this issue needs to be carefully addressed.
Literatures on this topic suggest two perceptives: a top-down, macro method
which starts the analysis from strategic requirement and a bottom-up, micro
method which focuses on product nature, quality, and lead time, etc. Kamann,
Harasek and El-Kadi (2001) proposed a P-O-P model in order to link the
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purchasing function with the general business strategy of a company. They
maintain that companies as an open system formulates a business strategy
based on external environment and internal competence. This strategy will be
translated into certain Policy (P), and the Organizational design (O) and
business Process (P) of each function in the company. Since purchasing has
transformed from only a business function into strategically important activities,
the purchasing policy, purchasing organization and purchasing process
should be coincide with the general business strategy. Therefore, in order to
select the item to purchase from outside parties, the first consideration will be
what the core competence is, so the company should keep in-house, and
what should be purchased in order to better use the specialty and other
benefits from the suppliers.
On a micro level, Andersson et al. (2007) used a multiple case study method
to link product characteristics and low cost country sourcing. They maintain
that Volume of the sourced product and the demand pattern are the dominant
forces to be studied in LCCS. Their primary finding is that products
considered for LCCS are characterised by high volumes, low level of design
changes, regular demand/regular shipments and high value density. Meredith
Smith (1999) summarized the selection criterion into six categories, namely
product specification and its change, product technology and its change,
impact of quality failure, impact of logistics, product criticality and volatility and
product/delivery cost.
Fisher (1997) classifies products into two categories and matched them with
two types of supply chain designs. Functional product (long life cycle, low
profit margin, good prediction for demand, low product variety, low
requirement for lead time) is suitable for an efficient supply chain, which aims
to supply predictable demand efficiently at the lowest possible cost. In
contrast, an innovative product (unstable environment, unpredictable demand,
short life cycle, high risk for stock out, high requirement for responsiveness)
requires a responsive supply chain, which strives for fast speed and more
flexibility. In the situation of Low Cost Country Sourcing, due to the long
transportation distance, hence long lead time and low responsiveness are
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inevitable, it seems reasonable that a simple, functional product with an
efficient supply chain is appropriate.
Beside the above factors, the order frequency and bath size should also be
considered. Product needed on a daily or weekly basis is better sourced
locally to prevent delivery disruption and inventory build-up. On the other hand,
items that are only purchased on a once a year scale is not proper neither,
since a stable relationship with suppliers is hard to maintain and supplier
search is very time-consuming. Large batch size is necessary in order to
reduce unit transportation cost. Furthermore, quality is always a big concern
for purchasers, especially under low cost country sourcing, because there are
certain stereotypes that product from low cost countries are not satisfied.
Therefore, it is better to choose those products which have less probability of
quality failure, high tolerance towards quality failure and less application in the
whole production process.
In addition, it is necessary to study the cost model of purchased product and
build a link with the low cost country. Multinationals join LCCS for the low
production cost, especially low labour cost; therefore, it is reasonable to
purchase the products which have more share of labour cost. According to
IBM Global Business Service (2006), component with low complexity and high
labour costs usually present the best opportunity for savings in the low cost
countries. Fraering and Prasad (1999) proposed a contingency model to link
sourcing and logistics strategies and they maintain that product with high
proportion of material cost is suitable for low cost country sourcing, because if
materials cost is high, a firm would be unable to reduce its expenses
significantly by just minimizing managerial overhead. Therefore, it must seek
external or international suppliers who may provide the materials at a lower
price (Cavusgil et al., 1993; Nichols and Taylor, 1995). To summarize the
literature, Figure 2 combines both top-down and bottom-up views and
summarize the selection criterion and characteristics for LCCS.
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Figure 2 Low Cost Country Sourcing product selection criterion
2.4 Sustainability of the low cost
Investigating which countries are currently cheap to purchase provides a part
of the evidence for decision making. What also important is to study whether
the low cost is sustainable in the medium and long term, which means the
saving potential should be significant for a period of 3 to 5 years. This issue
should be considered because it is important to maintain a stable and reliable
relationship with a long distance supplier, and LCCS must become a long
term strategy instead of a “one-time deal”. In addition, it is noticed that in
recent years, the labour cost in certain low cost countries have been
increasing with a fast pattern. For example, the average wage level of
manufacturing sector in China increased 12.93% from 2001 to 2007
accompanied with its fast economic growth (ILO Global Wage Report 2008-
2009). These changes cause some multinationals withdraw from China and
look for other low cost countries. Therefore, it is necessary to investigate the
sustainability of the low cost in the host country to prevent optimistic
businesses.
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Why the production costs are low in certain countries? Why the low cost is
relatively stable in certain period? And why after that period the production
costs increases rapidly? These phenomenon are witnessed in the Far East
world after World War II. The “demographic bonus” theory in demography
provides some systematic explanations. “Demographic bonus” is in the form
of a large group of working-age people supporting relatively fewer older and
younger dependents that creates a one-time opportunity for growth (window
of economic opportunity), may have accounted for as much as a third of the
East Asian economic miracle (The Economist, March 15th 2003). It explains
the relationship between Age Structure Transition (AST) of the population in a
country with its economic development.
There are two factors which influence age structure transition, namely fertility
rate (the average number of births per woman per lifetime) and mortality rate
(the total number of deaths per year per 1000 people). Furthermore, the
population is classified into 3 age groups: children (0~14 years), working age
adult (15~64 years) and elderly (65+ years). One key indictor which monitors
age structure transition is the dependency ratio. The “total dependency ratio”
is calculated by using the sum of children and the elderly divided by amount of
working age adult. 1 According to research (Sedano, 2008; Wong, 2005;
Navaneetham, 2002; Mari Bhat, 2001; Hussain, 2002, Chu & Lee, 2000), the
process of age structure transition goes through several stages: I. Mortality
begins to decline, causing an increase of children in the population, which
increases the total dependency ratio; II. Fertility then begins to decline, which
initiates a period of declining child-dependency ratios and declining total
dependency ratios. Working Age Adult accounts for the largest proportion
while life expectancy keeps increasing. III. Finally, the elderly population
begins to increase, and then elderly dependency ratios and total dependency
ratios rise again, so the society becomes aging. Fertility rate drops to around
2, which is a natural replacement for the population to stay stable. If the
fertility rate is lower than 2, the total population of that country will decrease.
1 Total dependency ratio has two components: children-dependency ratio and elderly-dependency ratio.
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As an example, Figure 3 shows the Age Structure Transition in Brazil in the
form of demographic pyramid.
Figure 3 Age Structure Transition in Brazil Source: Wong, 2005, “Demographic bonuses and the challenges of the Age Structure
Transition in Brazil”, data originally from United Nations (2003)
Total dependency ratio is a measurement of the burden of working age adult
to support the children and the elderly. It is reasonable to believe that stage II
of the Age Structure Transition provides the most abundant supply of labor.
This has many influences for the macroeconomic development. Sedano (2008)
summarized contributing effects of stage II. First, when a “baby booming”
generation enters the 15~64 age cohort, labor supply per capita rises. Since
women tend to have fewer children, female work participation rate increases.
These factors elevate per capita production levels and provide a supply-side
boost to the economy. Second, given that young people are in general net
borrowers, so Working Age Adults tend to save their earnings. This provides
potential resources for investment, which in turn leads to economic
development. Thirdly, given that life expectancy gets longer, a longer life
creates the belief that educational investments will yield a higher return,
therefore, education participation rate tends to increase. This will improve
education level of the whole population which acts as a powerful engine for
long term economic development. To sum up, the stage II of AST is a gift or
“bonus”. If a country could grasp this opportunity, it can enjoy a “golden age”
for economic development.
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The process of age structure transition is a slow process in most developed
countries, which took approximately two centuries to complete. But it is
witnessed that this process happened faster in certain developing countries,
especially after WWII, such as in East and Southeast Asia. There are some
strong evidences which show that demographic bonus contributes
significantly for economic development. Some economic miracles in Asia such
as Japan and China are a typical Beneficiary of this bonus. Statistics show
that demographic bonus contributes for 27% of the fast economic
development of China in the past 20 years. Research also shows that for the
whole Asia, the contribution of age structure change to economic growth from
1970 to 1990 is around 14%. (Bloom, Canning and Malaney, 1995, appendix
table 4b) However, demographic bonus is only a necessary but not sufficient
condition for economic take-off. If the policy makers of the country cannot
create enough employment opportunities for the large labor supply, it will lead
to massive unemployment, poverty, rampant crime, civil unrest and other
social-economic problems.
Because the whole population will gradually move to stage III, the
demographic bonus is a “window of opportunity”. It will happen once and only
once. A demographic window opens as the numbers of younger children
decrease, and the signal of diminishing window is the rise of total dependency
ratio which is contributed by the rise of elderly dependency ratio. When the
window is closed, the bonus will become onus, because of the aging of the
large amount of Working Age Adults. In that case, the economy will have
heavy burden due to social security cost to elderly people. Therefore, it is very
important for the countries which are still in the bonus window to build a
proper social security system.
There are other factors which facilitate the effect of demographic bonus, and
migration plays an important role. Peng and Cheng (2005, page 4) argue that
there are differential regional patterns of demographic dynamics and
consequent conditions of demographic bonus. Internal migration is the bridge
to match the conditions of harvesting demographic bonus in both sending and
receiving areas, and therefore could prolong the time span of harvesting
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demographic bonus in the urban areas, while provide opportunities for the
poor rural areas to be able to harvest demographic bonus, which results in a
win-win situation.
The implication to policy makers of developing countries is that, they must
develop a proper strategy for the country to fully utilize this one time
opportunity. It is important to create sufficient demand by open up the
economy and integrate with international trade. By exporting cheap labour,
the low cost country can accumulate capital for future development. For
multinationals, the implication of Demographic Bonus does not restrict to
international purchasing, but other activities such as outsourcing, local
production and other forms of FDI.
To summarize the literature, the reason that production cost is low mainly
because there is abundant supply of labour for a period of time, while total
domestic demand does not increase dramatically. This low cost is relatively
stable in a period due to the effect of Demographic Bonus. When the window
of opportunity is closed, labour becomes a scarce production factor and
therefore cost increase significantly. When the management of MNEs makes
decision for LCCS, accessing the countries’ current cost level is a part of the
input. What is more important is to investigate whether that country is enjoying
demographic bonus and until when. When both sides of stories are heard, a
final list of candidate countries could be generated.
2.5 LCCS decision process model
After a systematic description of important steps when making decisions for
Low Cost Country Sourcing, the decision process model is summarized in
Figure 4. The model is developed by using the method from SqEME®
Process Management (R.C.G. van Velzen, J.N.A. van Oosten, Th. Snijders
and T.W. Hardjono, Kluwer, Deventer, 2002). The model consists the
following main steps: (1) product to purchase are proposed based on
company strategy, (2) specific items are identified based on selection criterion,
(3) evaluate the current attractiveness of low cost country by using the TCO
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model, (4) analyze how sustainable the low cost in the future, (5) finalize the
country list and search for suppliers, (5) based on real quotation price, start to
develop suppliers in the low cost country. In the model, the process starts with
a diamond and it ends with a triangle. Each box represents one major process.
The incoming arrow from the left represents input, and the outgoing arrow
under the box represents the output. The above arrow represents the control
activities. The contents in the red dish line indicate the main research
objectives of this study.
Figure 4 Decision process model for LCCS based on TCO view
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3. The Case
Given that there is limited literature to apply Total Cost of Ownership into Low
Cost Country Sourcing, this study has an exploratory nature. Therefore, case
study is one of the proper strategies. By using case study, the business
practice in one company is systematically analyzed and the result is also
influenced by that specific industry. To conduct the research, both qualitative
and quantitative methods are used. Especially, a serial of interviews with
structured and semi-structured questions were performed with the managers
in the company. They are regarded as experts in their work fields. During the
interviews, the Delphi method was applied. By using the Delphi method,
common agreement of interviewees towards certain issues is used to derive
principles, while different opinions are excluded.
The European plastic pipe industry is chosen to carry out the case study. The
plastic pipe industry has growing potentials on the market, since plastic pipes
are replacing previous generations of concrete and metal pipes. The research
is carried out in a Dutch company called SMIT. SMIT Group is the leading
European supplier of plastic pipe system with operating activities in 28
European countries and over 6700 employees. The company operates in
several market segments in the plastic pipe industry, including tap water,
surface heating and cooling, soil and waste, rain- and storm water, distribution
of drinking water and gas and telecom applications. These businesses are
organized in two Strategic Business Units: Building & Installation and Civil &
Infrastructure. SMIT’s activities focus on Europe, but it has long history and
extensive experience on global sales through agents and selling know-how
through licensing.
SMIT’s strategic objectives include: being the leading supplier of plastic pipe
systems and solutions, focusing on European market, investing in innovation
and providing customers with large range of products and services. Evaluated
by the typology of strategy proposed by Porter (1985) which includes Cost
Leadership, Differentiation and Niche-Focus, SMIT’s strategy can be
22
classified as Differentiation, because it provides a package of product and
service so that customers can do “one stop shopping” when they seek plastic
pipe solutions. The high value-added service is supported by large investment
in innovation, and being a service provider also puts SMIT the high end of the
value chain. When looking at the nature of the pipe and fitting industry, the
market demand depends on the housing and construction market. The
change of product technology is relatively slow and the product life cycle is
long. Once the system is installed, warranties are provided for up to 50 years.
Besides, across Europe, each region (e.g. Southern Europe, North West
Europe, Central Europe, Nordic Europe, etc.) has its own requirement for pipe
system due to climate conditions or tradition of use. This requires different
materials and product design issues. Given these factors, SMIT group is
managed in a decentralized way and a large range of product portfolio is
maintained to meet various market demands. However, this practice brings
challenge for complexity management and optimization of the product
portfolio.
In recent years, SMIT has been optimizing its supply base by creating some
competitions between suppliers. In order to further trigger this process and
take the advantage of low cost countries, SMIT stepped out of local sourcing
and began to purchase from China. The products that currently purchased
from China are mainly steel and brass parts, such as valves, fittings,
connectors and manhole cover. The total savings based on landed price
varies from 20% to 50%. According to Management’s experience, product
quality is the major concern. Quality levels of different suppliers vary a lot.
Products from some suppliers are good and impressive, and for others, it
takes time to train the supplier to reach SMIT’s quality standard. It is also
important to maintain a local purchasing office in China to coordinate the
activities, perform quality control and the follow-ups. However, the increase of
labour cost of China in recent years gives a warning signal, so management
wants to search for backup sources. Therefore, the management questions
are: which other low cost countries can SMIT purchase from and how
sustainable the low cost can be?
23
4. Product selection for LCCS
According to the process model, several product items must be selected as
carriers In order to carry out the research. Firstly, the purchasing managers
from one region of the group had a brainstorm session and a list of product
family was generated. Secondly, serial interviews were conducted to ask the
opinions of purchasing managers from other regions. The results of the
interviews act as a screening process to narrow down the product list to 5
product families. These are:
- Brass valve: normally with a brass body and nickel coating on the surface;
- Brass fitting: mainly used for connecting pipes, similar material as the
valve;
- Grating: a kind of metal cover of the drainage, raw material is cast iron;
- Rubber Ring: mainly used in water applications for sealing;
- Plastic end caps: insert at the end of a pipe to protect it, used for packing
purpose.
NAICS Name of the
Industry Material Labour
Manufact.+
overhead
General
Sales +
Adm.
Profit
before
taxes
326122 Plastics Pipe and
Pipe Fitting
Manufacturing 55% 9% 14% 20% 2%
339991 Gasket, Packing,
and Sealing
Device
Manufacturing 38% 16% 18% 26% 2%
332919 Other Metal Valve
and Pipe Fitting
Manufacturing 41% 15% 15% 25% 4%
331522 Nonferrous
(except
Aluminum) Die-
Casting Foundries 31% 18% 33% 16% 2%
326199 All Other Plastics
Product
Manufacturing 40% 14% 23% 20% 3%
Table 2 Cost models of selected product on industry level
Source: De Nederlandse Vereniging voor Inkoopmanagement (NEVI)
24
The industry-wide (according to North American Industry Classification
System) cost models for these products are provided in table 2. As shown in
the table, share of material cost for the proposed products are quite high.
Their shares of labour cost are also higher than Plastics Pipe and Pipe Fitting
Manufacturing. According to the product selection criterion discussed in
section 2.3, it shows that it is wise to purchase those proposed products from
low cost countries.
Afterwards, a survey is conducted to the purchasing managers by using a self
administrated questionnaire. The questionnaire is designed based on the
Smith method (1999). In his contribution, he proposed a method to evaluate
the proper purchasing areas for products with different characteristics by
using multiple case studies. Different domains of supply market include local
sourcing (travelling distance within 50 km or 60 min.), national-wide sourcing,
sourcing within trade-bloc (such as EU) and finally purchase globally. For
global purchasing, purchasers could choose to buy directly or go through a
local agent. A questionnaire was designed based on the six categories of
considerations discussed in section 2.3. Respondents were asked to score
from -10 to 10 for the questions, and the weighted average score was
calculated. The results were plotted into a matrix, which is shown in figure 5.
In the case of SMIT, this is a useful tool to assess whether the selected item
are really suitable to purchase globally.
Finally, one specific item was chosen from each family. These items are
technically simple in order to lower the risk in the initial phase of LCCS. The
intention is that if the “trail product” could reach significant saving effect from
low cost countries, then more similar items could be purchased from that
country to take full advantage.
25
Figure 5 Smith matrix (Smith, 1999, page 124)
The questionnaire contains 18 questions. The purpose of the survey is
threefold. The first 2 questions are designed to learn whether the product
specification (e.g. drawing) and product cost model are available within the
company, not for calculation. Questions 3 to 17 are used to gather the
opinions towards 5 aspects: nature of product characteristics and its change,
purchasing volume and frequency, impact of quality, volatility/ criticality and
freight vs. product value density. The object of evaluation is the product family,
not any specific item or article. Respondents are asked to give a rating from 1
(in favour of local sourcing) to 5 (in favour of low cost country sourcing), and
the results will be converted to -2~2 in order to plot the coordinate into the
matrix.
Question 18 is a multiple choice question with 3 answers required. It is
designed to ask purchasing managers which 3 of the above aspects should
receive more consideration when they choose to do LCCS. The result of this
question will be used to determine the different weight of each aspect for the
calculation. Although the design of questionnaire is based on the Smith
method, the way of measuring is adjusted for the specific situation of SMIT
and the plastic pipe industry. Please refer to Table 3 for the questions and
their attributes of dimensions when plotted on the matrix.
26
There are two aspects mentioned by Smith but are not included in this model,
namely product technology and product availability. The reason is, according
to the interview with managers, the production technology for the 5 proposed
products are relatively basic in the manufacturing sector, such as forging, cast
(moulding), extrusion moulding and injection moulding. The degree of
complexity of these technologies does not vary significantly therefore it will
have little influence on the survey result. Secondly, given that the
technologies are relatively basic, they should be available in most of the
industrialized and transition economies. Therefore, these two aspects are
excluded from the model; instead, the issue of purchasing volume and order
frequency are emphasized by the model, because for low value-added
product, the way to realize saving from global sourcing is from high volume
and large batch size.
Question categoryQuestion categoryQuestion categoryQuestion category QuestionQuestionQuestionQuestion Dimension in Dimension in Dimension in Dimension in the matrixthe matrixthe matrixthe matrix
commodity or customized X simple or complex product X change of specification Y
Product characteristics and its change
speed of product life cycle Y purchasing Volume per year X Purchasing Volume
and frequency order frequency Y probability of quality failure Y degree of impact towards failure Y degree of tolerance to failure X Quality impact
easy of correction X degree of demand fluctuation X delivery disruption impact X Volatility/criticality Range of application of the product Y transportation volume per full container X Freight/product value
density purchasing price per weight Y
Table 3 questions in the survey and their correspondence dimension in the Smith matrix
27
Non-random sampling is used to select the respondents of the questionnaire
because they must be experts of the proposed purchasing items. The
respondents include group lead buying managers who have a general view of
corporate purchasing, and local strategic buyers who have more in-depth
views of each region. Regarding the number of questionnaires, 5 were
designed and sent out for brass valve, 6 for brass fitting, 4 for metal grating, 5
for rubber ring and 3 for plastic end caps. In total, 23 questionnaires were sent
out to 11 purchasing managers and 21 respondents were received. One of
them had insufficient answer so it was excluded for analysis. Therefore, a
valid response rate is 87% which is sufficient.
Findings
The answers to question 18 shows the following result: regarding the top 3
consideration for LCCS, among the 11 purchasing managers, 8 of them chose
Quality, 7 voted Purchasing volume and order frequency, 5 for product nature,
5 for Volatility/criticality and 3 for Freight/product value density. This gathered
opinion is not product-specific but is in general for LCCS. The number of
“vote” is used directly as the weight of its corresponding aspect. The results of
question 3 to 16 were converted from the scale [1, 5] to [-2, 2]. Finally, the
weighted average of X and Y dimensions were calculated for each product
family, and the results are shown in Table 4.
Table 4 findings of the questionnaire based on Smith method
Product Product Product Product naturenaturenaturenature
Volume/Volume/Volume/Volume/ frequencyfrequencyfrequencyfrequency QualityQualityQualityQuality Volatility/Volatility/Volatility/Volatility/
criticalitycriticalitycriticalitycriticality
Freight/Freight/Freight/Freight/ product product product product costcostcostcost
∑∑∑∑
ValveValveValveValve 0.5,0.5 -1,-0.3 -1.67,0.17 -0.67,-0.7 1.7,0 -0.7,0.05 FittingFittingFittingFitting 1,-0.2 0.2,0.6 -0.8,-0.2 -0.5,0.2 1.6,0 -0.04,0 GratinGratinGratinGratingggg 0.5,0.75 -1.25,0.25 -0.5,0.36 -0.75,2 1.75,-2 -0.3,0.47 Rubber RingRubber RingRubber RingRubber Ring -0.13,0.63 1.75,-1 -1.63,-0.38 -1.13,-2 1.25,-0.25 -0.5,-0.4 Plastic end Plastic end Plastic end Plastic end capcapcapcap 1.8,1.3 1.7,-1.3 -0.5,1.3 -0.7,-2 1,1 0.4,0.45
28
The result in the above table shows that, first, purchasing managers think only
plastic end cap is a very suitable product for global sourcing. Valve, fitting and
grating should be purchased from national trade bloc, in this case, the EU.
Rubber ring product is best to purchase from local suppliers. Second, the
findings do not show a significant direction about proper purchasing areas,
because the final coordinates are all very close to the origin point. Therefore,
one conclusion from the calculation is that purchasing those 5 kinds of
product globally is not strongly supported by the result. This is out of the
expectation of the researcher, which could either caused by the design of
research or the data input.
Going back to the original data, it is interesting to find that purchasing
managers’ opinions towards whether the product should be sourced globally
is heterogeneous. Respondents voted for the same direction on certain
consideration aspects, but in some cases their opinions are completely
opposite (e.g. one votes 2 while another votes -2). Table 5 shows the
distribution tendency of data by calculating standard deviation for each
question and each product. According to the table, in some cases, the
standard deviation is around 1.5 within a scale of [-2, 2], which indicates that
purchasing mangers do not have a consensus towards that issues.
ValveValveValveValve FittingFittingFittingFitting GratingGratingGratingGrating Rubber RingRubber RingRubber RingRubber Ring End capEnd capEnd capEnd cap sample sizesample sizesample sizesample size 3333 5555 4444 4444 3333
Q3Q3Q3Q3 1.000 0.548 0.577 0.816 0.000 4444 0.000 0.447 1.291 0.957 0.577 5555 0.577 0.894 0.957 0.500 0.000 6666 1.155 1.789 1.500 1.000 2.309 7777 1.000 1.304 0.957 0.500 0.577 8888 1.155 1.517 0.500 0.816 0.577 9999 0.000 0.894 0.500 0.957 0.000 10101010 0.577 0.447 1.155 0.000 1.528 11111111 0.000 1.643 1.258 1.000 1.000 12121212 1.155 1.304 1.500 0.500 0.000
29
13131313 1.155 1.414 0.500 1.258 0.000 14141414 0.577 0.707 0.957 0.000 1.155 15151515 1.528 1.789 0.000 0.000 0.000 16161616 0.577 0.548 0.500 0.957 1.000 17171717 1.000 1.000 0.000 0.957 1.000
Table 5 Standard deviation of data for each question
The findings that purchasing those products from low cost countries is not
significantly supported and the fact that these purchasers’ opinions are
heterogeneous can be explained by the following reasons. First, low cost
country sourcing is still in the initial phase within SMIT. Due to organizational
inertia, some purchasers are not ready to move the supplier base or they are
not fully convinced that LCCS can work within this organization. Second,
SMIT’s purchasing activities are managed in a de-centralized way in order to
adjust to requirement of local market. Each market has different product
portfolio. Therefore, for the same brass fitting, for example, the volume could
be huge in one region but limited in another.
When evaluating this model and data collection, some weaknesses are
identified. First, the sample is small. For each product family there are only 3
to 5 relevant purchasing managers as respondents. However, this problem is
difficult to overcome in this case, given that the sample is non-random and
respondents are deemed to have expert experience. Second, under each
product family, there is a large product portfolio, and those specific articles
possess different characteristics and requirement, therefore, asking
respondents to evaluate based on a product family level could be re-
considered.
30
5. Low cost country selection
It is difficult to generate a list of low cost countries by using one single
quantitative threshold, e.g. GDP per capita, given that the concept and
standard for “low cost country” is rather vague. Due to limited time for the
study, it is planed to have a final list with 5 countries. Therefore, when
generating the long list by looking around the globe, 4 areas are identified and
around 5 countries were picked from each area. Table 6 shows the list of
candidate countries.
Asia Latin
America Mediterranean Area Emerging
Europe
China Argentina Morocco Bulgaria
Indonesia Brazil Tunisia Romania
India Chile Egypt Croatia
Philippines Mexico Turkey Czech
Viet nam Poland
Slovakia
Hungary
Ukraine
Table 6 List of candidate countries for LCCS
Those countries were selected because they are frequently mentioned by
business practitioner as destination of LCCS. China will be in the final list as a
benchmark of comparison, in order to see whether other countries are better
places for SMIT to purchase than from China. “Emerging Europe” mainly
refers to former European socialism countries. These countries are joining the
integration process of European Union and it is witnessed that their
economies were growing fast in recent years.
The next step is to collect labour cost data for those 21 countries. It is
necessary to first distinguish the definition of labour cost from wage. The
primary stakeholder of labour cost is the employer. It is defined by the U.S.
Bureau of Labour Statistics (BLS) as (1) direct pay and (2) employer social
insurance expenditures and (3) other labour taxes. Wage cost, on the other
hand, only refers to the first part of labour cost, which is workers’ “take-home
money”. However, labour cost data are not widely available from a lot of
countries, mainly because the statistical capability from some developing
31
countries need to be improved. Furthermore, each country has its own
economic census standard and there is always a lag between latest data and
present, which make it less comparable. Therefore, data of wage cost were
collected instead, and data on non-wage cost were collected by other means
in order to measure it indirectly.
International Labour Organization (ILO), United Nations Industrial
Development Organization (UNIDO) and U.S. Bureau of Labour Statistics
(BLS) provide good database on wage cost statistics. The average earning
per month of employee (including all industries) based on local currency were
collected from the 21 countries and the Netherlands (as benchmark). Time
span includes 2001 to 2008 in order to find a comparable year, but the latest
year of available data from different countries vary a lot. Then the market
foreign exchange rates on Dec. 31st of each year were used to convert local
currency into the Euro. The conversion process did not involve Purchasing
Power Parity (PPP) adjustment, given that this study does not intend to
equalize the living standards across countries, but concerns how much the
employer should pay. Afterwards, the average monthly earning data are
compared with the Netherlands. The result shows how much lower of monthly
wage of that low cost country than the Netherlands. Table 7 presents the
results of comparisons.
Monthly Monthly Monthly Monthly earning EURearning EURearning EURearning EUR
% lower than % lower than % lower than % lower than NLNLNLNL
Year ofYear ofYear ofYear of 2222 referencereferencereferencereference
Source Source Source Source of dataof dataof dataof data
ArgentinaArgentinaArgentinaArgentina 384 86 2006 ILO MexicoMexicoMexicoMexico 310 89 2007 ILO ChileChileChileChile 398 85 2005 ILO BrazilBrazilBrazilBrazil 463 83 2006 BLS BulgariaBulgariaBulgariaBulgaria 164 94 2006 ILO RomaniaRomaniaRomaniaRomania 280 90 2006 ILO CroatiaCroatiaCroatiaCroatia 794 71 2006 ILO CzechCzechCzechCzech 671 75 2006 ILO
2 This is the year to be compared with Netherlands, within its correspondent database
32
HungaryHungaryHungaryHungary 683 75 2007 ILO SlovakiaSlovakiaSlovakiaSlovakia 596 78 2007 ILO UkraineUkraineUkraineUkraine 86 97 2004 UNIDO TurkeyTurkeyTurkeyTurkey 672 76 2006 other3 MoroccoMoroccoMoroccoMorocco 571 79 2005 UNIDO EgyptEgyptEgyptEgypt 108 96 2006 ILO TunisiaTunisiaTunisiaTunisia 305 88 2003 UNIDO IndiaIndiaIndiaIndia 113 96 2004 UNIDO VietnamVietnamVietnamVietnam 39 99 2008 other4 ChinaChinaChinaChina 163 94 2007 ILO PhilippinesPhilippinesPhilippinesPhilippines 128 95 2006 ILO PolandPolandPolandPoland 490 82 2006 BLS IndonesiaIndonesiaIndonesiaIndonesia 81 96 2008 other5
Table 7 Result of wage data and comparison with Netherlands
The TCO model for low cost country selection has been discussed in section
2.2. When applied in SMIT’s case, the model is extended by using more
detailed indicators. The complete model is shown in Table 8, together with the
weight of each indicator. The weights were determined based on purchasing
managers’ experience of current China sourcing practice. Statistics for the
indicators are all from sound database, especially the Global Competitiveness
Report 2008-2009 (World Economic Forum) which provides the rankings of
very comprehensive indicators for 144 countries. Logistics data (cost and lead
time) are based on real quotation from the transportation company.
There are two kinds of data: hard data are directly collected from the
database, and index data are extracted from the Global Competitiveness
Report 2008-2009 (country ranking from 1~144). Then these original data are
converted into a score within a range of 1 ~ 10. The original score for each
country is attached in the appendix 2
3 Turkish Statistical institute, press release 2006
4 Vietnamese Statistical bureau
33
Table 8 Low Cost Country selection model: indicator and weight
Model dimension
Indicator Direct measure Type of data
Source of data
Wage cost level (70%)
Wage per month,% lower than NL
Hard
ILO, UNIDO, BLS,etc.
Labor Cost, 35%
Non-wage labour costs (30%)
Social security payment and payroll taxes as a percentage of worker’s salary
Index
Global Competitiveness Report (GCR)
Manufacturing Value-added, average annual real growth rate (2000-2006) - 33%
Hard
UNIDO
Manufacturing Value-added per capita, at constant 2000 US$ prices(2006) - 33%
Hard
UNIDO
Industrial performance (30%) Manufacturing Value-added as
percentage of GDP at constant 2000 prices(2006)- 33%
Hard
UNIDO
Quality of primary education - 33%
Index
GCR
Primary school enrolment rate - 33%
Index GCR
Primary education (10%)
Government Education expenditure - 33%
Index
GCR
Higher education and training (30%)
Index
GCR
Competence, 20%
Innovation (30%)
Index
GCR
ISO ownership ratio (50%)
The percentage of manufactures that receive ISO certificates
Hard
Enterprise survey
Quality, 15% Supplier quality
rating (50%)
Index GCR
Logistics cost 6(20%)
Hard
Maersk or Schenker
Transportation time (30%)
Hard
Maersk or Schenker
Time to export (days) (25%)
Hard
www.Doingbusiness.org
Cost to export (15%)
US$ per container
Hard
www.Doingbusiness.org
Infrastructure rating (10%)
Index
GCR
Logistics, 20%
* Special duty
(If Applicable)
Hard
EU trade commission
5 Vietnamese Statistical bureau
6 Common transportation destination for comparison: a factory in the Netherlands
34
IPR (15%)
Intellectual property protection
Index
GCR
Efficiency of legal framework - 25%
Index
GCR
Transparency of government policymaking - 25%
Index
GCR
Business costs of crime and violence - 25%
Index
GCR
Institutions (20%)
Ethical behaviour of firms - 25%
Index
GCR
Macroeconomic stability (15%)
Index
GCR
Total local tax rate - 33%
Index
GCR
Number of procedures required to start a business - 33%
Index
GCR
Goods market efficiency (10%)
Time required to start a business - 33%
Index
GCR
Technological readiness (10%)
Access rate to telephone, mobile and internet, etc.
Index
GCR
Local supplier quantity - 33%
Index GCR
State of cluster development - 33%
Index
GCR
Business sophistication (10%)
Production process sophistication - 33%
Index
GCR
Social Responsibility (10%)
Child labour use - 10%
Hard
UNICEF
Business Environment, 10%
Corruption (10%)
Corruption Perceptions Index (CPI) - 10%
Index
Transparency International
Table 8 Low Cost Country selection model: indicator and weight (continued)
Some explanations of certain indicators/direct measures are necessary. The
first dimension only considers labour cost in this case, although there are
other cost factors such as raw material and energy. This is because raw
materials for the proposed products, such as brass, rubber and iron are
commodities, and they have a “world price” which means the price of different
countries will not differ significantly. Data on energy cost, on the other hand,
are not quite available on a country level. Given that labour cost is normally
used by academics and practitioners as a lead indicator for low cost country, it
35
is reasonable to only consider labour cost in this case. The input for wage
cost level is the result shown in table 7. Non-wage labour cost is measured by
the percentage of social security payment and payroll taxes in worker’s salary.
These two indicators receive 70% and 30% weight respectively, because the
former one comes from hard data and the later on comes from index data.
Given that index is an indirect way of measuring, hard data is believed to be
more reliable and therefore receives more weight.
The dimension of Competence aims to measure “what can they do?” of a
country on a general level. Industry performance monitors the capability of a
country’s industrial sector and the key indicator is Manufacturing Value-Added
(MVA). Primary education is involved aiming to check the knowledge level of
front line workers. It should be a qualifying factor and therefore only receives
10% attention. Higher education and Innovation aim to examine a country’s
research and development capability and therefore receive more attentions.
Quality, which is an important issue, receives 15% of weight in the whole
model. This is not a signal that quality is not important. Quality can only be
judged based on real product and assessing the quality level of a country is
difficult. ISO ownership ratio tests whether quality management system is
prevalent in a country and supplier quality rating is based on survey to
management executives which is performed by Global Competitiveness
Report. However, these two indicators have relatively weak measurement
validity. For example, it is observed that companies can “purchase” the ISO
certificate in some countries and ISO certification has become a fashion and a
qualifying factor to stay in business. Therefore, the quality dimension is
assigned with less weight to prevent bringing bias to the result.
In the logistics dimension, special duty should be stressed. It is designed in
the model to check: 1) is there any anti-dumping duty levied by the European
Union against certain low cost country; 2) is there any favourable tax policy
made by the low cost country which facilitates the company to purchase, such
as no import tax under Free Trade Agreement. This is a “yes or no” option
and therefore does not receive a weight in the model.
36
The last dimension concerns the environment for doing international business.
These indicators are also cost drivers for purchasing, especially when the
company wants to set an establishment (e.g. a local purchasing office) in the
host country. This dimension receives less weight because the model tends to
focus more on tangible cost, but they cannot be ignored. In order to clearly
show the share of weight for each indicator, Table 9 provides their impact
factor to the final result.
Impact factor
Wage per month,% lower than NL 24,5%
Non-wage labor costs 10,5%
Industrial performance 7,0%
Primary education 1,0%
Higher education and training 6,0%
Innovation 6,0%
ISO ownership ratio 7,5%
Supplier quality rating 7,5%
Logistics cost 4,0%
Transportation time 6,0%
Cost to export 5,0%
Time for export 3,0%
Infrastructure rating 2,0%
Intellectual property protection 1,5%
Institutions 2,0%
Macroeconomic stability 1,5%
Goods market efficiency 1,0%
Technological readiness 1,0%
Business sophistication 1,0%
Social Responsibility 1,0%
Corruption 1,0%
Table 9 Impact factor of each dimension to the final result
Findings
The following table shows the result of calculation as a ranking of
attractiveness for LCCS. The wage data is also shown at the right side box as
a comparison of attractiveness when wage is the only consideration.
37
Attractiveness for LCCS
Wage lower than NL, %
Indonesia 6,79 Vietnam 98,8
India 6,67 Ukraine 97,0
China 6,62 Egypt 96,0
Chile 6,46 India 96,0
Tunisia 6,22 Indonesia 95,7
Egypt 6,19 Philippines 95,0
Philippines 6,07 Bulgaria 94,0
Romania 5,87 China 94,0
Czech 5,82 Romania 89,7
Viet nam 5,81 Mexico 89,0
Poland 5,64 Tunisia 88,0
Bulgaria 5,52 Argentina 86,0
Mexcio 5,24 Chile 85,0
Ukranie 5,22 Brazil 83,3
Turkey 5,17 Poland 82,3
Morocco 4,98 Morocco 79,0
Slovakia 4,98 Slovakia 78,4
Argentina 4,83 Turkey 76,0
Hungary 4,79 Czech 75,3
Brazil 4,74 Hungary 75,2
Croatia 4,56 Croatia 70,8
Table 10 Country selection result: Attractiveness for LCCS
Given that the design of weight is the key factor to determine the ranking of
countries, in order to ensure the validity of the model, a sensitivity analysis is
performed by adjusting the weight of certain indicators. The above weight
system (table 8) belongs to Model C, which is considered most suitable for
final use. Model A and B and their relevant country ranking are shown in
Appendix 2. The calculation based on un-weighted average is also performed.
When comparing Model A, B and C, it is found that the “top 5 country”
remains the same, although their ranking against each other slightly changes.
The second group of countries (number 6~10) and the bottom 5 countries are
also nearly the same. Therefore, there is no dramatic change of ranking when
altering the weights. Comparing Model A, B, C with the un-weighted model, it
finds that certain countries on the top and the bottom remain at the same
position, while positions of countries in the middle range change. This implies
that the indicators’ scores of top (bottom) countries are consistently high (low)
38
and cannot be significantly influenced by the design of weight. Countries in
the middle range could score high on certain indicators while score low on
others, therefore their ranking can be influenced by the design of weight. The
above sensitivity analysis shows that the design of measurement is
reasonable and valid, and it is also a process of fine-turning the model design
in order to find the most suitable one for decision making.
When looking at Table 9, the result of country selection model shows that,
certain country is very attractive when only consider the wage (and labour)
cost, however, when a TCO view is taken, that country could look less
attractive, such as Vietnam and Ukraine. This shows the importance of taking
a total cost view. Besides analyzing the ranking of countries, it is also
necessary to “open the black box” and find out which country is good at what.
This is to investigate which of the 5 aspects (labour cost, competence, quality,
logistics and business environment) contribute the most to a country’s
attractiveness for LCCS. The best candidate country should score high on all
aspects and its performance is relatively balanced. If a country scores high on
one or two aspects but low on others, it brings some concerns for
management decisions. The break-down view is shown as a Radar Chart for
each country which is attached in the Appendix 3.
The results show that among countries of Mediterranean region, Tunisia is the
most attractive country, although it scores relatively low on quality aspect.
Morocco and Egypt show significant advantage on logistics service, but other
aspects need to be improved. Turkey’s labour cost is a disadvantage. Among
Asian countries, China, India and Indonesia are all attractive. China has the
most balanced radar shape among all countries, while India and Indonesia
need to improve on quality and business environment. Vietnam and
Philippines’s low labour cost is very attractive, but other aspects show some
risks. Countries in Latin America have relative balanced performance on 5
aspects, but all score relatively low. Countries in “Emerging Europe” show
good performance on several aspects, except on labour cost. Actually labour
cost is becoming a disadvantage for them as a low cost country.
39
The issue of special duty should be discussed separately. The 21 countries
could be classified into 2 groups. Countries which are members of EU have
the advantage of no import duty when purchasing from there. Rate of import
duty for other countries varies from 2.2% to 5.7%, depends on the product to
purchase. No anti-dumping duty or sage guard measures are found against
the product to purchase. Regarding policy benefit from host country on
international trade, Chile has signed Free Trade Agreement with EU;
therefore, there is no import duty from Chile.
This model has certain weakness. First, given that certain data (minority in the
whole dataset) are difficult to collect, some indicators are not directly
comparable, which decrease the reliability of the calculation. Second, this
model assesses countries on an aggregate level by taking all industries or
sectors. It cannot make an evaluation for specific industry; therefore, this
model can only give a general direction. Whether the savings from LCCS
could be realized depends on the actual situation of that industry.
The benefit of this model is that it could be used for repetitive decision making.
The weights are tailor made for this company and in the future the model
could be used to search for other countries.
40
6. Sustainability of low cost country sourcing
Based on the theoretical guideline of demographic bonus, a model is
developed to briefly analyze the sustainability of low cost in the 21 countries.
The model intends to study the “window” in the following way: first, in order to
analyze when the bonus window will close for each country, population data
of the 21 countries are collected from international database of U.S. census
bureau, and then dependency ratio (children, elderly and total) are calculate
from the year 1990 to 2030 (estimation data). Population growth rate of these
years is also collected as a reference. These statistics are compared and
received a score from -2 to 2. Table 11 provides an overview of data and
scores. For the threshold of assigning scores, please refer to Appendix 4. The
original data of dependency ratio are presented as line chart and they are
provided in the Appendix 5. Second, urbanization rate is used as a
measurement of population migration. Urbanization rate of the 21 countries at
the year of 2020 are collected, and the rate is compared with the urbanization
rate of developed economies, afterwards they received a score from -2 to 2.
For the threshold of assigning scores, please refer to table A3 in the appendix
4. The design of threshold is only for the purpose of differentiating those
countries on that indictor. Those two scores will be used to calculate the
weighted average score, but the weight of each aspect is different. Age
structure transition (AST) has the fundamental influence; therefore, it receives
80% of the weight, while migration as a facilitating factor receives 20% of
weight.
the Year that TDR begins to rise
Population growth rate at 2025
Score - size of window
India 2030 + 1,2 2 Egypt 2030 + 1,8 2 Turkey 2028 1,1 2 Mexico 2024 1,0 2 Philippines 2030 + 1,8 2 Indonesia 2024 1,0 2
41
Vietnam 2024 1,0 2 Morocco 2022 1,0 1 Argentina 2030 + 0,9 2 Brazil 2024 1,0 2 China 2012 0,5 0 Tunisia 2016 0,8 1 Chile 2016 0,8 1 Romania 2012 -0,2 -1 Hungary 2010 -0,3 -1 Croatia 2014 -0,1 -1 Poland 2012 -0,2 -1 Slovakia 2012 0 -1 Czech 2008 -0,2 -1 Ukraine 2012 -0,7 -2 Bulgaria 2008 -0,9 -2
Table 11 size of bonus window: overview of data and score
Finally, in order to measure whether the low-cost country are making good
policies to grasp the gift of demographic bonus, the country ranking from
Global Competitiveness Report (2008) is used as input data because it
includes comprehensive factors of a country’s development. The ranking is
converted to a score of [1, 10] and then divided by 10, so that the result of
calculation acts as a factor of multiplication. It is multiplied to the weighted
average result of first two aspects. The full calculation model is shown in table
12 and the calculation follows the formula:
Final score (G) = E*F = (A*B+C*D)*F
42
size of window
A
Weight
B
urbanization rate at 2025
C
Weight
D
Score
E
Policy and institution
quality
F
Sustainable Purchasing
Score
G
India 2 80% 2 20% 2,0 0,7 1,40 Indonesia 2 80% 1 20% 1,8 0,7 1,26 Egypt 2 80% 2 20% 2,0 0,5 1,00 Vietnam 2 80% 2 20% 2,0 0,5 1,00 Turkey 2 80% 0 20% 1,6 0,6 0,96 Mexico 2 80% -1 20% 1,4 0,6 0,84 Brazil 2 80% -1 20% 1,4 0,6 0,84 Philippines 2 80% 0 20% 1,6 0,5 0,80 Tunisia 1 80% 0 20% 0,8 0,8 0,64 Morocco 1 80% 1 20% 1,0 0,5 0,50 Argentina 2 80% -2 20% 1,2 0,4 0,48 Chile 1 80% -2 20% 0,4 0,9 0,36 China 0 80% 1 20% 0,2 0,8 0,16 Romania -1 80% 1 20% -0,6 0,6 -0,36 Hungary -1 80% 0 20% -0,8 0,6 -0,48 Croatia -1 80% 0 20% -0,8 0,6 -0,48 Poland -1 80% 0 20% -0,8 0,7 -0,56 Slovakia -1 80% 0 20% -0,8 0,7 -0,56 Czech -1 80% 0 20% -0,8 0,8 -0,64 Ukraine -2 80% 0 20% -1,6 0,5 -0,80 Bulgaria -2 80% 0 20% -1,6 0,5 -0,80
Table 12 calculation of sustainable purchasing score
Findings The above results should draw some attentions for management decision
towards LCCS. China, the very hot destination for low cost sourcing and
outsourcing, positions at the middle of the list. China has been enjoying the
demographic bonus since middle 1980s’ and at this moment it is at the edge
43
of stepping out of the window. Certain research in China estimates that the
bonus effect will end at 2015 (Pool, Wong and Vilquin, 2006). This explains
why it is witnessed that labour cost in China has been increasing significantly.
Countries like India, Egypt, and Philippines are in the prime of the bonus. It is
estimated that the window of opportunity could be open until 2025 or 2030.
Given that India is actively participating in globalization and adjusting its policy
to create a good environment for economic development, it is an attractive
country regarding sustainable low cost purchasing. Other Asian countries,
such as Vietnam and Indonesia also have the potential, but there policy
environment should be improved. Countries in Latin America are in the bonus
window but the size of window is different for each country. Argentina could
still enjoy the window until 2030. Brazil and Mexico could step of out the
window around 2025. However, the window for Chile could close soon at
around 2015. It is also deemed that Latin American countries are not utilizing
this one time gift very well except for Chile. The governments must try to
make better policy to increase employment and improve economic
environment, otherwise the gift will be wasted (Sedano, 2008).
Countries in “Emerging Europe” are not attractive regarding sustainable low
cost sourcing. It is witnessed that the population growth rate has been
negative in recent years, which means in near future, those countries will
experience shortage of labor. The reason that labor costs in those countries
are relatively low is not due to the effect of demographic bonus. Those
countries are about to pass the window. Rather, it is because their
economies are recovering from the negative effect of central planning regime.
Given that those countries have joined the EU (or will do in near future), it is
believed that their economies will closely integrated with more advanced
economies in Europe, so it can be expected that the labor cost will increase
fast in near future.
It is important to note that there are other factors which influence the
dynamics of production cost development. Age Structure Transition provides
the fundamentals, so this is a reasonable model to briefly analyze the
tendency. However, the stages of age structure transition can differ on
44
regional levels in a country, so countries that are geographically big have the
possibility to prolong the bonus window. The effect of demographic bonus on
specific industry can also be different. For example, garment and toy
production business can feel more cost pressure than equipment
manufacturing when the bonus window closes. The valuable benefit of
demographic bonus theory is that it can be applied not only for low cost
purchasing, but also for outsourcing, local production and other forms of
foreign direct investment (FDI).
7. Discussion of results
7. 1 Discussion of LCCS country selection
According to the LCCS decision making process model, the final country
selection should combine the results of both total cost view and sustainable
purchasing findings. Therefore, in order to integrate the result of section 5 and
6, a final calculation is performed by adding up the score of TCO country
selection and the score of sustainable purchasing. Result of calculation and
ranking of countries are provided in Table 13. Ranking of countries when only
consider the current situation is also shown at the right hand box for
comparison purpose.
Ranking when
consider the future
TCO country selection
score
Sustainable Purchasing
Score Final Score
Ranking when only consider
current situation
India 6,67 1,40 8,07 Indonesia
Indonesia 6,79 1,26 8,05 India
Egypt 6,19 1,00 7,19 China
Philippines 6,07 0,80 6,87 Chile
Tunisia 6,22 0,64 6,86 Tunisia
Chile 6,46 0,36 6,82 Egypt
Vietnam 5,81 1,00 6,81 Philippines
China 6,62 0,16 6,78 Romania
Turkey 5,17 0,96 6,13 Czech
Mexico 5,24 0,84 6,08 Vietnam
Brazil 4,74 0,84 5,58 Poland
Romania 5,87 -0,36 5,51 Bulgaria
45
Morocco 4,98 0,50 5,48 Mexico
Argentina 4,83 0,48 5,31 Ukraine
Czech 5,82 -0,64 5,18 Turkey
Poland 5,64 -0,56 5,08 Morocco
Bulgaria 5,52 -0,80 4,72 Slovakia
Ukraine 5,22 -0,80 4,42 Argentina
Slovakia 4,98 -0,56 4,42 Hungary
Hungary 4,79 -0,48 4,31 Brazil
Croatia 4,56 -0,48 4,08 Croatia
Table 13 Final calculation of LCCS country selection
By comparing the two rankings, some interesting findings emerge. First, India,
Indonesia and Tunisia remain as top 5 countries in both rankings, which imply
that for those three countries, not only they are attractive destination for LCCS,
but the low cost is sustainable in the medium term (3~5 years). The positions
of Vietnam, Philippines and Egypt are promoted after considering sustainable
purchasing issue, which means they are also worth being considered by
management for investment in the long term, but with more caution. It is
important to note that the ranking of China and Chile are lowered down when
consider the future. This shows that in the near future, labour cost in these
countries could increase significantly. They are getting less competitive for
low cost sourcing given that their economies are experiencing transition from
cheap production factor driven to innovation driven, which means they are
getting more attractive for other types of foreign investments. Other Latin
American countries rank in the middle range of final calculation. Those
countries are still enjoying the demographic bonus, but a lot of work should be
done to improve the economic and business environment, and they are more
suitable for Northern American companies to do LCCS. Countries in
“emerging Europe” score at the bottom mainly because the low cost is not
sustainable in the near future.
This whole process of low cost country selection can provide a guideline for
management decision making regarding where to go, however, it does not
show a “black or white” answer. A lot of practical issues must be taken for
consideration. For example, although Indonesia shows attractiveness on both
cost side and sustainable purchasing side, purchasing managers are rather
46
conservative to go to this country, mainly due to the problem of corruption
based on their practical experience. Although corruption has only 1% impact
power in the TCO country selection model, when comes to detailed business
matters, it could act as a major barrier. Therefore, management can use the
decision making process model as a useful tool to get general direction, but
final decision making needs to consider other risks which cannot be directly
assessed by the model.
In order to test the effectiveness of the whole country selection model, the
company began to search for suppliers in India, Tunisia and Turkey. Within
limited time, several quotations of different products were received from
suppliers. Although judging from the initial price offer no significant saving can
be obtained from those suppliers, this is not regarded as a signal that the
whole selection model is invalid. Instead, it is attributed to the fact that those
suppliers are from unknown business network. Receiving an opportunistic
offer from a “cold contact” is common in purchasing practice. Therefore,
further supplier searching and development are required.
Based on the above result, when it comes to the management decision of
which country to go, it is recommended that big country is relatively good
choice. By “big country” it refers to size of territory and also the scale of
economy. The reason is that, firstly, countries with large territory normally
possess various and abundant natural resources, which ensures the country
to be independent on resources consumption. Secondly, Countries with large
territory normally have unbalanced situation among different areas regarding
economic development and age structure transition, such as China, India and
Brazil. For example, the eastern costal regions of China are more developed
than inland areas and attract most of foreign investment. The population of
some costal provinces have finished age structure transition and are
becoming aging, while inland provinces can still enjoy the demographic bonus.
There have been certain researches on the relationship between industry
agglomeration, cost of production factors and industry upgrading. According
to Fujita and Krugman (1999) and Krugman (1991), firms tend to cluster
47
together for the benefit of firm-level scale economies and reduced
transportation cost and congestion cost, so that they can serve large local
markets from a few plants. When firms are drawn into one cluster, the local
land becomes scarce resource so land price intends to rise. Given that living
cost in the agglomeration area (normally big cities) is higher than peripheral
areas, therefore, firms need to offer higher labour compensation to attract
workers. The effect of industrial agglomeration also contributes to the
inequality of development among different areas. Statistics of wage
development in China shows that the 2008 average wages in coastal
provinces 7 is 35.2% higher than interior provinces (China Statistical Year
Book, 2008). Therefore, due to industrial agglomeration, cost of production
factor, such as land rent and labour cost will gradually rise. Then this
industrial cluster will become less cost competitive, therefore, these firms tend
to relocate to less developed areas, and the developed area will experience
industry upgrading, normally from manufacturing to service business. For big
countries with unbalanced development situation, there is much more room to
relocate the low cost driven industries. Since this process is relative slow, the
increase of cost for the whole country is also slower than small country.
Besides, countries with less scale on economies, such as Vietnam and
Thailand, can be relatively easier be influenced by global economic crisis.
Examples include the Asian financial crisis happened in 1997 and recent
economic crisis of Vietnam in 2008.
7.2 Discussion of organization issue
In section 4, the finding of item selection for low cost country sourcing shows
that, purchasing managers’ opinions on whether a product should be
purchased from a low cost country are much diversified. The original answers
from respondents show that some purchasers provide strong support while
some others are rather conservative. This is a signal that Low Cost Country
Sourcing, as new purchasing practice, is not widely accepted by purchasers in
7 Coastal provinces include Beijing, Tianjin, Liaoning, Shanghai, Jiangsu, Zhejiang, Shandong, Fujian,
Guangdong and Hainan. Other provinces are classified as interior provinces.
48
the company. Therefore, it is important to find out what is hindering the
progress and provide a solution.
Kamann and Bakker (2004,2007) did a long term research to study how does
a new purchasing practice spread in a company, and why does this process
differs between different companies. A framework called contagion process is
proposed and there are many factors influencing this contagion process.
Firstly, purchaser’s personal trajectory together with various networks that
they have been through contributes to the way that the purchaser believes
how purchasing practice should be organized. Secondly, due to corporate
culture or tradition, a company has its own way of “getting things done”, which
is a process of social negotiation, and everybody comply with this social order.
This way of doing business is defined as Socially Negotiated Order (SNO).
Therefore, even if the purchaser has his/her own opinion on purchasing
practice in some cases, they need to follow the SNO. However, there are
exceptions. The purchasing function has different social status in companies.
Normally companies in fashion industry of trading business pay more
attention to the voice of purchasing, but in other industries, purchaser still
does not have high weight in management decisions. The social status of
different functions in companies is defined as Negotiated Social Order (NSO).
If a purchaser could gain higher status in the NSO in a company, he/she can
pervade the management in order to put his opinion towards organizing
purchasing into business practice, in order to influence the SNO.
In addition, according to Argyris and Schon (1978), the adoption and diffusion
of new practices—and therewith the process of contagion— is also hindered
because of a discrepancy between what people say and what they do. If
people talk about applying new practices while still doing it in the old way,
others in the network will not notice a change. This weakens the evidence of
the effectiveness of applying the new idea. The discrepancy can be the result
of (1) unclear commutation of the new purchasing practice within the
organization, enabling people to use their “old” methods whilst talking about
the “new” purchasing practice because they misinterpret the concepts and
their meaning, since they do not fit their frame of reference; (2) resistance
49
because of uncertainty of the new method and its effects, where people will
use the rhetoric for external promotional ends or keeping their management
satisfied and at a distance. (Kamann and Bakker, 2004, page 62).
Based on the observations of the researcher, when analyzing the LCCS
practice in SMIT by applying the contagion process model, it is found that the
purchasing function does not have a strategic role for the company, which
means the status of purchasing is not very high in the Negotiated Social Order.
This is still common in a manufacturing company. Regarding the Socially
Negotiated Order, the company does have its tradition or habit on purchasing.
The purchasing function is organized in a functional way, while a lot of
modern enterprises are moving towards a process oriented design. The
working styles of purchasers are more individualized instead of coordinated
as teams. The purchasing manager responsible for LCCS is in charged of this
job mainly because his has extensive experience with some Asian countries
when he worked there, and he sees more benefit of LCCS than people who
do not have this experience. This is related to personal career trajectory and
business networks. Some peer purchasing managers show conservative
opinions mainly because the result and effectiveness of LCCS are not well
communicated to them, so they still have high concern towards the risk side of
LCCS and they are reluctant to follow this practice. Top management does
have support for LCCS, but the message of support is not very clear to the
whole company, therefore, peer purchasing managers and other functions are
not sure how will the company plan to dedicate resources to LCCS in the
future. Furthermore, the current practice of LCCS is project based and is
executed by certain purchasing managers on a part time basis. A formal
documented business process and organizational design is not in place yet.
To summarize, the current barriers to progress on LCCS come from (1)
unclear message from top management regards the attitude and strategic
planning of LCCS; (2) lack of communication about the effectiveness of LCCS
and its benefits; and (3) lack of proper organization design to support LCCS,
such as formal business process and team work coordination.
50
It is recommended to the management that, firstly, the practice and
experience from China Sourcing could be summarized and reviewed, and a
clear course of action for the future LCCS is necessary. It would be more
effective to send this message out of the board room so that purchasing
managers and other functions understand what will happen. This also gives
conservative people certain reason to revaluate the effectiveness of LCCS. It
is necessary that they can acknowledge the benefit and support it with
motivation, not accepting the decision by coercion. Regarding the
organizational support, depending on the vision of management, the
development can follow a route that is from project based to process based;
from “coordinated individual” to project team and finally forms a separate
business function for LCCS; from part time managers to full time resources.
By this means, there will be clear Task, Responsibility and Authority among
employees and this also creates a better platform for sharing information in
order to increase the efficiency of work and avoid misunderstanding. In
addition, when analyzing LCCS practice of SMIT by applying the continuum
model of different levels of global sourcing (introduced in literature part), it can
be concluded that, taking Europe as a whole, SMIT is in the stage of “engage
in international purchasing as needed” (level 2) and it is moving towards the
stage of “international purchasing as part of sourcing strategy” (level 3). In
order to take the full advantage of global sourcing, it is necessary to build
cross disciplinary teams which involve functions such as purchasing,
engineering and production.
It can be expected that it is a slow process for people to accept Low Cost
Country Sourcing in the purchasing function, and sometimes this comes with
resistance. In order to make it more effective to change people’s minds, one
recommendation is to apply the Soft System Methodology (SSM) proposed by
Peter Checkland. SSM is an organized process of inquiry, based on systems
modeling, which leads to choice of purposeful action (Checkland, 1985, page
822). The primary use of SSM is in the analysis of complex situations where
there are divergent views about the definition of the problem — "soft
problems". When facing a problem, people have different views on the causes,
solutions and other issues, or in short words, people have different
51
perceptions about the real world. SSM makes these perceptions explicit by
using inquiry and system modeling, so that people can understand each other
what they think towards this problem. There is no “right” or “wrong” description
of these human activities and thoughts, only multiple taken-as-given images
of the world. Based on the explicit opinions, people can have open discussion
and debate, and the intentions is to let people accommodate each other
between different or conflict opinions. This process cannot eliminate conflicts,
but it does enhance the communication and understanding between each
other, and hopefully can achieve a consensus. The SSM process can be
executed via several sessions of workshops, in this case for example,
purchasing managers are encouraged to disclose their opinions about LCCS,
topics like whether it is suitable for SMIT, what is the proper practice to
organize LCCS and so on. Top management can participate to learn
manager’s opinions and this is also a learning and even a brainstorm process
for everybody.
8. Conclusion
This study aims to answer two management questions regarding Low Cost
Country Sourcing: (1) which countries offer low cost sourcing opportunities?
And (2) Is it attractive to purchase from that low cost country in the medium
and long term? Given that there are currently limited literatures in this field, a
case study method is used in one European plastic pipe system manufacture.
In order to conduct the research, the selection criterion of suitable product for
LCCS is summarized from literature, and a matrix calculation method is
applied by using data from a questionnaire survey to purchasing managers.
This method aims to gather the opinions of purchasers whether a product is
viable for LCCS.
Secondly, a country selection model was built based on the Total Cost of
Ownership principle. The model has 5 dimensions: labour cost, competence,
quality, logistics and business environment. It is designed to evaluate the
52
current attractiveness of certain countries as destinations of low cost sourcing.
At the same time, In order to assess whether the low cost is sustainable in the
medium and long term, an analysis of countries’ Age Structure Transition was
performed based on the theory of Demographic Bonus. The analysis intends
to make a brief estimation about when the low cost window in a sourcing
country will diminish.
These main steps of analysis are integrated into a decision process model for
Low cost Country Sourcing. During the research, 21 deemed low cost
countries were evaluated, and a ranking of attractiveness for those countries
is provided after the calculation. When considering the current low cost
attractiveness and sustainable purchasing in the future, the recommended top
five countries include (in descending order): India, Indonesia, Egypt,
Philippines, and Tunisia. Vietnam, Morocco, Turkey, Argentina, Mexico, and
Brazil also have the potential. China is indeed an ideal destination compared
with other low-cost country, but it is losing the low cost attractiveness
gradually in the medium term. The whole evaluation model provides a general
reference of direction for LCCS, given that the model assesses indicators on a
macro level. There are a lot of other factors which influence the dynamics of
low cost development on a micro level; also, the industry-specific situation
could differ from the general result. Generally it is recommended to
management that going to big countries (in the respect of territory and scale
of economy) are better choice, because (1) big countries have relatively
abundant resources and (2) the economic development and age structure
transition of population in big countries are normally unbalanced, which
provide more possibilities to prolong the process of low cost development.
During the research, it was found that purchasing mangers’ opinions
regarding whether the proposed product should be purchased from low cost
countries were not homogenous. Deeper investigation reveals that this is a
reflection that not every purchaser in the company is convinced about the
benefit of LCCS. This could reduce the efficiency and effectiveness of LCCS
practice in the future. Observations show that there should be clear message
from top management regarding the course of action towards future LCCS,
53
and a proper business process and organizational design should be in place,
in order to create a better platform for communication. Soft System
Methodology (SSM) is recommended as a means to disclose people’s
perception of LCCS in order to acknowledge and accommodate each other’s
opinion, which could act as a way to improve communication.
In general, the LCCS decision process model provides a “one package deal”
for purchasers and management regarding low cost country sourcing
decisions. It is a generic model and can be used for repetitive decision making.
Regarding the validity of the methods, they are grouded on sound academic
literatures. The sources of data are all from professional database, mostly are
international organizations, therefore, the data input are deemed to be reliable.
Although there are difficulties to collect data for international comparison,
sensitivity analysis shows that this issue will not significantly influence the
validly of the whole model. The weakness of this evaluation model is that it
provides country assessment on a macro level but it is not industry specific.
Further research is suggested to focus on the topics such as: (1) what is the
relationship between product nature and benefit of LCCS? Namely will
(technically) simple or advanced product bring more purchasing savings? (2)
What is the relationship between the nature of industry (or business) and the
benefit of LCCS? Namely what kind of business will benefit more from low
cost country sourcing, while what kind of business is not recommended to do
LCCS?
54
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58
Appendix 1 Original score for LCCS country selection
Egypt Turkey Tusinia Morocco Ukraine Slovakia Romania
Wage per month,% lower than NL 10 3 7 4 10 4 8
Non-wage labor costs 3 4 4 5 1 2 2
Industrial performance 2,31 3,3 2,64 2,31 4,95 6,6 4,29
Primary education 3,9 3,9 7,8 4,8 4,8 5,4 5,1
Higher education and training 4 5 9 4 6 7 7
Innovation 6 6 9 6 7 6 5
ISO ownership ratio 2 5 1 1 1 3 4
Supplier quality rating 3 7 7 4 4 7 4
Logistics cost 10 9 10 9 1 10 7
Transportation time 9 8 4 10 7 5 8
Time for export 9 9 8 9 1 4 10
Cost to export 8 6 8 8 4 2 4
Infrastructure rating 6 6 8 6 5 6 3
Intellectual property protection 6 4 8 5 2 6 6
Institutions 7,25 5 8,5 6,25 3 5,25 3,25
Macroeconomic stability 1 5 5 4 4 7 5
Goods market efficiency 7,26 7,2 5,61 6,93 4,62 5,61 7,59
Technological readiness 4 6 7 5 6 8 7
Business sophistication 5,61 6,93 7,92 5,61 5,28 6,93 5,28
Social Responsibility 6 8 5 4 6 8 10
Corruption 1 7 6 4 1 7 5
59
Appendix 1 (Continued)
Poland Hungary Czech Croatia Bulgaria Philippines Vietnam
Wage per month,% lower than NL 5 2 2 1 9 9 10
Non-wage labor costs 4 2 2 5 3 9 5
Industrial performance 5,28 5,28 7,92 3,96 4,62 3,3 5,61
Primary education 6,9 5,7 6 6 4,8 3,6 3,9
Higher education and training 8 8 9 7 6 6 3
Innovation 6 7 9 7 3 5 6
ISO ownership ratio 4 6 10 4 2 1 1
Supplier quality rating 6 6 9 5 5 6 3
Logistics cost 10 10 10 6 7 7 8
Transportation time 5 5 3 9 7 1 5
Time for export 8 7 8 6 5 8 4
Cost to export 7 3 6 4 1 8 8
Infrastructure rating 3 6 7 7 4 4 4
Intellectual property protection 5 7 7 6 3 4 4
Institutions 3,75 4,5 4,75 5 2,5 3,5 5,75
Macroeconomic stability 7 2 7 6 7 7 5
Goods market efficiency 5,61 6,6 5,94 6,6 5,94 2,64 4,29
Technological readiness 7 8 8 7 7 5 5
Business sophistication 5,94 6,27 8,91 3,96 4,29 5,28 5,94
Social Responsibility 8 8 8 8 8 3 1
Corruption 7 8 8 6 5 1 1
60
Appendix 1 (Continued)
Indonesia India China Argentina Mexico Chile Brazil
Wage per month,% lower than NL 10 10 9 6 7 6 5
Non-wage labor costs 8 5 1 3 4 10 1
Industrial performance 5,28 3,3 7,59 5,28 3,3 3,96 3,3
Primary education 4,5 4,2 6 5,4 4,2 2,7 4,2
Higher education and training 5 6 6 6 5 7 6
Innovation 7 8 9 3 4 6 7
ISO ownership ratio 2 2 6 3 1 1 1
Supplier quality rating 6 8 6 6 7 9 8
Logistics cost 7 10 9 1 4 6 1
Transportation time 7 4 3 7 2 6 9
Time for export 6 8 6 10 8 6 9
Cost to export 8 6 10 2 2 8 4
Infrastructure rating 4 5 7 4 6 8 5
Intellectual property protection 3 6 7 2 5 6 5
Institutions 4,5 6,75 6,5 1,5 3 7,5 2,75
Macroeconomic stability 5 3 10 6 7 10 2
Goods market efficiency 3,63 3,3 2,97 2,64 5,61 7,26 1,32
Technological readiness 4 5 5 5 5 7 6
Business sophistication 6,93 8,91 7,92 5,28 6,27 7,92 8,25
Social Responsibility 8 3 4 6 1 9 7
Corruption 1 4 5 2 5 10 4
61
Appendix 2 Sensitivity Analysis of country selection models
Table A1. Sensitivity analysis: Different models of weight design
62
Appendix 2 (Continued)
Table A2. Sensitivity analysis: Ranking from different weights design
63
Appendix 3 Break-down analysis for each low cost country’s performance
64
Appendix 3 (continued)
65
Appendix 3 (continued)
66
Appendix 3 (continued)
67
Appendix 3 (continued)
68
Appendix 3 (continued)
Appendix 4 Threshold of assigning scores to demographic bonus study
1. To study when the bonus window will close:
� If population growth is positive: TDR8 begins to rise at around 2012 � 0
TDR begins to rise at around 2025 � 1 TDR begins to rise after 2025 � 2
� If population growth is negative: population growth rate < -0.5 � -2
-0.5 < population growth rate < 0 � -1 2. To compare urbanization rate development:
In the year 2020, by using the urbanization rate of developed country as a benchmark, If, urbanization rate is around 70% � 0
35% < urbanization rate < 45% � 2 45% < urbanization rate < 60% � 1 urbanization rate is around 80% � -19 urbanization rate is around 90% � -2
8 Total Dependency Ratio
9 When cities are over populated (common in Latin American countries), it brings challenges to the
administration of cities and this has negative effect on social-economic development.
0.00
0.20
0.40
0.60
0.80
1.00Cost
Competence
QualityLogistics
Business environment
Croatia
69
2020 2020 2020
Egypt 45% Bulgaria 74.80% Mexico 80.70%
Morocco 61% Czech 75% Argentina 93.80%
Tunisia 71.20% Hungary 72.30% Brazil 89.50%
Turkey 74% Poland 62.40% Chile 91%
Romania 58.1%
China 53.20% Slovakia 59.80% Developed country 77.50%
India 34.30% Ukraine 69.90%
Indonesia 62.60% Croatia 61.60%
Philippines 72.30%
Viet Nam 34.70%
Table A3 urbanization rate at the year 2020 Source: World Urbanization Prospects, UN population division
Appendix 5 Data of dependency ratio development
Note: the red cycle indicate the year that the effect of demographic bonus begins to diminish
Dependency ratio Czech
0
0.1
0.2
0.3
0.4
0.5
0.6
1992
1996
2000
2004
2008
2012
2016
2020
2024
2028
Child
Old
Total
70
Dependency ratio Argentina
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependency ratio Chile
0.000
0.100
0.200
0.300
0.400
0.500
0.600
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependency ratio Brazil
0. 0000. 1000. 2000. 3000. 4000. 5000. 6000. 7001990 1994 1998 2002 2006 2010 2014 2018 2022 2026 2030
Chi l dOl dTot alDependency ratio Mexico
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
0.800
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
Child
Old
Total
71
Dependency ratio Turkey
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
0.800
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependency ratio Tunisia
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
0.800
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependency ratio Egypt
0. 0000. 1000. 2000. 3000. 4000. 5000. 6000. 7000. 8001996 2000 2004 2008 2012 2016 2020 2024 2028
Chi l dOl dTot alDependency ratio Morocco
0. 0000. 1000. 2000. 3000. 4000. 5000. 6000. 7000. 8000. 9001990 1994 1998 2002 2006 2010 2014 2018 2022 2026 2030
Chi l dOl dTot al
72
Dependency ratio China
0.000
0.100
0.200
0.300
0.400
0.500
0.600
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependency ratio India
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
0.800
1992
1996
2000
2004
2008
2012
2016
2020
2024
2028
Child
Old
Total
Dependency ratio Indonesia
0. 0000. 1000. 2000. 3000. 4000. 5000. 6000. 7001990 1994 1998 2002 2006 2010 2014 2018 2022 2026 2030
Chi l dOl dTot alDependency ratio Vietnam
0. 0000. 1000. 2000. 3000. 4000. 5000. 6000. 7000. 8000. 9001990 1994 1998 2002 2006 20102014 2018 2022 2026 2030
Chi l dOl dTot al
73
Dependency ratio Philippines
0. 0000. 1000. 2000. 3000. 4000. 5000. 6000. 7000. 8000. 900199019941998 20022006201020142018 202220262030
Chi l dOl dTot alDependency ratio Bulgaria
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependency ratio Hungary
0.000
0.100
0.200
0.300
0.400
0.500
0.600
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependency ratio Poland
0.000
0.100
0.200
0.300
0.400
0.500
0.600
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
74
Dependency ratio Romania
0.000
0.100
0.200
0.300
0.400
0.500
0.600
1992
1996
2000
2004
2008
2012
2016
2020
2024
2028
Child
Old
Total
Dependency ratio Slovakia
0.000
0.100
0.200
0.300
0.400
0.500
0.600
1992
1996
2000
2004
2008
2012
2016
2020
2024
2028
Child
Old
Total
Dependency ratio Ukraine
0.000
0.100
0.200
0.300
0.400
0.500
0.600
1990
1994
1998
2002
2006
2010
2014
2018
2022
2026
2030
Child
Old
Total
Dependecny ratio Croatia
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
1992
1996
2000
2004
2008
2012
2016
2020
2024
2028
Child
Old
Total