SUBJECT: UNCERTAINTY SUPPLY
CHAIN MODEL AND TRANSPORT IN ITS
DEPLOYMENTS
Fabiana Lucena Oliveira
Universidade do Estado do Amazonas, Brazil
E-mail: flucenaoliveira@gmail.com
Submission: 14/11/2013
Accept: 28/11/2013
ABSTRACT
This
article discusses the Model
Uncertainty of Supply Chain, and proposes a matrix with
their transportation modes best
suited to their chains. From the detailed analysis of the matrix of uncertainty, it is suggested transportation modes best suited to the management of these chains, so that transport is the most appropriate optimization of the gains previously proposed by the original model, particularly
when supply chains are distant from suppliers of raw materials and / or supplies.Here
we analyze in detail Agile Supply Chains, which is a result of Uncertainty
Supply Chain Model, with special attention to Manaus Industrial Center. This
research was done at Manaus Industrial Pole, which is a model of industrial
agglomerations, based in Manaus, State of Amazonas (Brazil), which contemplates
different supply chains and strategies sharing same infrastructure of
transport, handling and storage and clearance process and uses inbound for
suppliers of raw material. The state of
art contemplates supply chain management, uncertainty supply chain model, agile
supply chains, Manaus Industrial Center (MIC) and Brazilian legislation, as a
business case, and presents concepts and features, of each one. The main goal
is to present and discuss how transport is able to support Uncertainty Supply Chain
Model, in order to complete management model. The results obtained confirms the
hypothesis of integrated logistics processes are able to guarantee attractively
for industrial agglomerations, and open discussions when the suppliers are far
from the manufacturer center, in a logistics management.
Keywords: Uncertainty Supply chain Model, Agile supply chain; Manaus
industrial pole; logistics, transport.
1
INTRODUCTION
Business Logistics, as a set of techniques and
activities-means (or support) for the productive operations of companies,
represents an area of technical-professional research and intervention with
increasing relevance to the systemic competitiveness of countries, regions,
economic blocks, sectors or individual companies. This growing relevance of
Business Logistics has been especially significant over the course of the last
thirty years.
It is justified by a global context marked by at least
four major phenomena: (I) the commercial and productive internationalization of companies, (II) the forming
of regional trade blocks and the acceleration of the process for economic,
political and cultural integration
between, and among, blocks (NAFTA, MERCOSUL, European Union, ASEAN,
etc.); (III) the radical and swift technological change brought about by the
advent of the new Communication and Information Technologies (CIT’s), the
frontline products of which are the Internet, mobile telephony and the
transition to the platform of digital convergence between computing and
telecommunications apparatus and equipment which, in conjunction, change the
way in which people and companies live, work and produce, and (IV) in the quest
for competitiveness in the CITs, trans-national companies have sought out the
emerging economies to house their factories, in the attempt to ensure cheaper
labor, lower taxes and other attractive advantages offered by the governments
of each emerging economy.
This being so, private and/or public logistics models
constitute an integral part of the solutions packages offered to companies,
regions and countries for equalizing or overcoming the conditions of current
market competition. In public and private economic agendas, Logistics have come
to stay.
Considering the Matrix of Uncertainty
Supply Chain Model: how transportation fits and supports
global competition of these matrices
and subsidiaries, since the source of raw material supply is far from
manufacturing industry?
As companies switch from being local to being
trans-national, the logistics challenge becomes increasingly bigger. If at the
start of the development of modern industries logistics was an activity
aggregated to Sales and marketing, as of the 1960s, logistics became a
fundamental activity for the survival of companies through control of storage,
stocks and the transpiration of materials. (BALLOU, 1993)
Within this environment,
the logistics strategies for the companies were developed in such a way as to identify the best forms of management for their
respective supply chains.
Logistics Strategies: an exploratory approach
The literature regarding Industrial Logistics underlines
a number of decision categories that need to be articulated between each other,
in such a way that companies are able to achieve the objectives with lower
costs and optimized services.
According to WANKE (2003), companies need to consider the
following categories:
Coordinating product flow: should product flow be pulled,
that is, set in motion by the link closest to the end consumer, or pushed, that
is, coordinated by the link closest to the initial supplier?
Production policy: should a company produce for stock,
based on future sales forecasts, or produce to order, always attending the real
demand, only when the client places the order?
Stock allocation: should stocks be centralized in a single
location, or decentralized in a number of installations?
Size of the installation network: how many installations
should a company have, where should each one be located and which products and
markets should be attended by each installation?
Choosing Modes of Transport: should a company operate
with slower and cheaper modes of transport, such as railways and ships, or
faster and more expensive, such as road and air? Should it seek to consolidate
transport or express delivery?
The answers to these questions will define the logistics
strategies to be adopted by each company, taken individually, and, based on
this, it would appear valid to seek an adaptation of the variables mentioned
above to define the logistics strategies for agglomerations such as Regional
Economic Centers.
According to DORNIER et al (2000), the traditional
financial performance measures (sales and profitability, for example) are
complemented by a set of operational variables that provide for better
understanding of how the logistics system should be analyzed. These operational
variables are: cost, quality, service and flexibility.
This
article presents an analysis of the state
of art of the Supply Uncertainty
Model (SCUM) categorizing their supply chains,
methodology and case study,
and even clusters model
used as a research source - Manaus Industrial
Center (MIC)
and agile supply chain used as a sample,
and the results as
well as to answer the question posed.
2
THE
SUPPLY CHAIN UNCERTAINTY MODEL (SCUM)
The Supply Chain Uncertainty Model (SCUM) was presented
to the academic community for the first time in 2002, and its uncertainty
matrix was used to characterize the processes for the supply of raw materials
and of demand (consumer market), via certain intrinsic characteristics of each
product. In general terms, the uncertainty model allows for the fact that that
there are some products that given their characteristic of stability (demand
and supply) will have a more simplified logistics strategy, and that there are
some products that, given their characteristics of instability (demand and
supply), very short life cycle and high aggregated technology, will require
special logistics strategies management.
Figure 1 reproduces the Uncertainty Matrix published in
the article entitled Aligning Supply Chain Strategies with Product
Uncertainties, in the California Management Review for the Year of 2002. This
study considered the supply chains of the products considered to be functional
and those considered to be innovative, in other words, products on the cutting
edge of technology. For each one of these products, a different management
proposal was presented, making it clear that products on the cutting edge of
technology have unstable processes from the point of view of demand (consumer
market) and supply (raw material), thereby giving rise to the Uncertainty
Model.
|
|
Uncertainty
of Demand |
|
|
|
Low (Functional Products) |
High (Innovative Products) |
Uncertainty
of Supply |
Low (Stable Process) |
Candies, basics, common apparel, foodstuffs, oil and
gas |
Fashion apparel, computers, audio, video |
High (Development Process) |
Hydroelectric apparatus, some food segments |
Telecom, high-end computers, semi-conductors |
Figure 1: The Uncertainty Matrix Source: Lee,
(2002) |
This being so, the products considered to present low
uncertainty of supply and low uncertainty of demand are those that aggregate
little technology in their production, in other words, the life cycles of these
products are usually longer and their manufacture depends on to a low degree on technological evolution. Whereas
those with low uncertainty of supply and high uncertainty of demand are the
audio and video, telecommunications and computer products that follow the
tendencies of a market characterized by the consumption of novelties that aggregate
new technologies, in the expectation of keeping up with technological
evolution. These products already usually present a short life cycle and
require agility in the management of their supply chains, since the tendencies
in technological evolution can be very fast.
Those products with high degrees of uncertainty in supply
and low degrees of uncertainty in demand are represented by hydroelectric
apparatus (electrical power generating equipment, equipment for hydroelectric
power stations, cables and connections and mining equipment, for example) and
some food segments that aggregate specific raw materials. The sources for the
supply of raw materials to manufacture these products are limited and this
leads to uncertainty of supply, since demand is stable and the need for
production remains Constant from a source with scarce supply.
Goods with a high degree of uncertainty in demand and a
high degree of uncertainty in supply are represented by telecommunications
products, high-end computers and semi-conductors. These products have sources
of even scarcer supply and that are sometimes monopolized by a handful of
companies. From the point of view of demand, telecommunications products,
largely represented by mobile telephony, have a short life cycle, high
competitiveness and a high degree of uncertainty regarding the consumer desire
to buy. Agility in the management of this supply chain is vital to the survival
of the product´s manufacture. Any economic agglomeration (cluster, industrial
district, technopolis) that wishes to include companies classified in the lower
quadrants of the Uncertainty Model needs to consider agility as one of its
pillars of development.
The strategies for the uncertainty models are classified
according to four types: (1) Efficient Supply Chains, (2) Supply Chains with
risk coverage, (3) Sensitive Soppy Chains and (4) Agile Supply Chains.
Figure 2, presents a summary of the supply chain
classifications:
|
|
Low (Functional Products) |
High(Innovative Products) |
Uncertainty
of Supply |
Low (Stable Process) |
Efficient Supply Chains |
Sensitive Supply Chains |
High (Development Process) |
Supply Chains with Risk Coverage |
Agile Supply Chains |
Figure 2: Supply Chain Strategies Source: Lee,
(2002) |
3
SUPPLY
CHAIN UNCERTAINTY MODEL AND ITS MAIN VARIABLES
According to Grieger (2002), the most important variables
to be analyzed for the Supply Chains in the SCUMs are: a) Fast Product Life
Cycle; b) Just in Time Production; c) Cost leadership; and d) Global
Competition.
The matrix for the uncertainty model classifies the
products as being innovative or traditional. The object of this study is the
innovative products), which are those with a short life cycle, high degree of
technological innovation and fashion contents, in other words, fashion related
characteristics and/or components that represent unpredictable demand. (LEE,
2002)
Table 1 presents a comparison, available in the
literature, between a company with a product considered to be
Functional/Traditional and a company with a product considered to be
Innovative.
Table 1: Product characteristics classified according
to the SCUM: Functional versus Innovative
Functional Product |
Innovative Product |
Low Uncertainty in Demand |
High Uncertainty in Demand |
More Predictable Demand |
Hard to Predict Demand |
Stable Demand |
Unstable Demand |
Long Life Product |
Short Selling Season |
Low Inventory
Cost |
High Inventory
Cost |
Low profit
margin |
High profit
margin |
Low product
variety |
High product
variety |
High volume per “pre-assembled kit” |
Low volume per
“pre-assembled kit” |
Low cost for
“lack of stock” |
High cost for
“lack of stock” |
Low Obsolescence |
High
Obsolescence |
Source: Lee, 2002
A functional product may be represented by a color TV,
for example. A traditional color TV, in other words, with a conventional image
tube, does not suffer major oscillations in demand, classifying it as more
predictable. An innovative product may be represented by the mobile telephone.
This product has an unstable consumer market (demand), a very short life cycle
(from six to eight months) and a high level of obsolescence, since it
aggregates new technologies very quickly. The profit margins are high, since
this product has high aggregated value, and this fact represents a high value
for the inventory to be managed.
Agility is understood as being the speed with which a
process can be concluded. One good example is the process of the unloading of
merchandize for customs inspection. An agile process will be concluded in two
hours, as occurs in some parts of Brazil, and in some models of international
economic agglomerations. Table 2, below, demonstrates, very simply, how the
variables discussed here are encountered in the different models of
agglomerations between countries:
Table 2: Variables for the Uncertainty Model in Industrial
Agglomerations
|
Brazil |
Mexico |
China |
Cost |
High |
Medium |
Low |
Agility |
Low |
High |
High |
Obsolescence |
High |
High |
Low |
Based
on the behavior of the variables exposed above, it is possible to understand
why Brazil has been facing difficulties in managing the Uncertainty Chain, in
comparison with its global competitors, for example.
The high level of obsolescence among these companies in
Brazil is largely justified by the low agility in responding to this logistic
chain, either to receive (import) raw materials, or re-export those raw
materials unused in the productive process, which explains the high cost
involved in a slow and overly bureaucratic supply chain.
Among the many models already identified by the
literature for classifying the supply chains, the SCUM is used to characterize
the industries whose products present uncertainty in demand and uncertainty in
the supply of raw materials as a fundamental characteristic. Here we underline
the universe of these companies in such a way as to identify how this model may
fit the reality of an industrial center (geographical delimitation), and of the
current customs legislation in this country, or in their respective
particularities.
With regard to the purposes, this survey was explanatory
and applied, because it aimed not only to clear up the factors involved, but
also to contribute to the making of decisions and propose concrete solutions to
concrete and immediate problems.
The universe for study refers to the group directly
involved in the formulation of the problem, the companies in the Manaus
Industrial Center (MIC). All of the variables involved in the process for
defining a consigned stock model for the MIC were an integral part of this
universe: a) reduction of inventory
cost; b) agility in the processes for importing raw materials and exporting
finished goods, c) reduction in international transit time, agility in
attending to the uncertainty models and d) identification of the different
logistics strategies for the companies installed in the MIC so as to categorize
this model of agglomerations.
The sample of the companies surveyed used the parameters
of their participation in the global indicators for the MIC in terms of
revenues, exports, imports and direct jobs and by their classification
according to the categories of the SCUM, these being stable processes and
innovative processes in the supply chains for functional and innovative
products.
The data was collected via: a) Bibliographical research
in books, specialist magazines, articles, theses and dissertations on the
chosen subject. All of the data required for the theoretical basis was
collected; b) Interviews with the people involved in the supply chain
management processes for the companies covered in the uncertainty model
examined in this study; c) Direct analysis of real times, based on the
measuring of processes involved in the logistics management chain, such as,
transit time, customs dispatch time and simulations of adapted models, based on
the proposed Brazilian customs legislation.
Analysis of the data included: a) tabulation of the real
times obtained in the companies analyzed, especially those working with
Telecommunications, based on the need for adapting the MICS and in such a way
that this data could be compared with that for the other companies; b)
Comparison between the times obtained within the companies analyzed and the
concept described in the supply chain management strategies, available in the
literature analyzed, in such a way as to demonstrate whether the practice is in
accordance with the concepts; c) Adaptation of the models suggested by the
literature, and also by the governing legislation in Brazil, to the supply
chain management models existing in the companies studied, in the aim of seeing
the improvements based on the development models available and approved by the
Brazilian regulatory agencies.
This analysis adapted and chose the Uncertainty Model in
its most extreme aspect uncertainty of supply and uncertainty of demand, using
an industrial unit that has its supply chain perfectly adapted to this reality
as its research universe.
The results obtained
here, therefore, are restricted to the industrial units with extreme
uncertainty regarding their supply chains, following the guidance of Brazilian
customs legislation, and improving the processes already identified as being
promising by the case study for the Brazilian customs authorities: The Manaus
Industrial Center (MIC).
5
CASE
STUDY: THE MANAUS INDUSTRIAL CENTER (MIC)
The Manaus Industrial Center (MIC) is the result of the
Model Free Trade Zone of Manaus (ZFM), created by the Federal Government and
made effective in 1967, with a geopolitical focus based on fiscal incentives
for production, and supervising three sectors: Industrial, Commercial and
Farming, based on the reduction of the logistical disadvantages inherent to the
Western Amazonian region. Its tax benefits (IPI industrialized products tax,
Import Tax and the ICMS goods and services tax) extend, according to different
regimes, to the States of Amazonas, Acre, Roraima, Rondônia and the Free Trade
Zones of Macapá and Santana, in the State of Amapá. This model, administered by
the Superintendence of the Manaus Free Trade Zone (SUFRAMA) for the last 40
years, attracted more than 450 industries to the MIC, many of which are
internationally known brands (some of these brands are NOKIA, GILLETTE,
COCA-COLA, SAMSUNG, LG, HONDA, SONY, PANASONIC, VIDEOLAR, SIEMENS, PHILLIPS,
etc.,) which jointly represent around US$ 4.0 billion in accumulated fixed
investments to date, and cover a number of sub-sectors, the foremost of which
are electro-electronics, information technology, two wheeled vehicles (bicycles
and motorcycles), chemistry, thermoplastics and watch making.
The recent performance of the MIC can be seen in Table 23:
Table 3: Recent performance indicators for the Manaus
Industrial Center (MIC)
INDICATOR |
PERFORMANCE IN 2007 |
1.
GLOBAL REVENUES OF
THE COMPANIES |
US$ 11.,5 billion |
2.
DIRECT JOBS GENERATED |
115 thousand jobs |
3.
ESTIMATE INDIRECT
JOBS |
510 thousand jobs |
4.
EXPORTS |
US$ 0.855 million |
5.
TOTAL TAX GENERATED |
US$ 2.8 billion |
6.
COMPANIES CERTIFIED
VIA ISO 9000 |
251 |
From
the importance
of the SCUM for the Amazon region, and considering that the main supply chains of raw materials and inputs that feed this
industrial agglomeration, are in the East, and the basis for reception and processing of these materials
is in the West, which requires
a transport logistics
management, despite the distance and
dependence on more efficient transportation, we must be a global competitor.
Thus the figure four proposed
mode of transportation that best suits their supply
chains, in the quest for efficiency
proposed in the original model.
|
|
Low (Functional Products) |
High(Innovative Products) |
Uncertainty
of Supply |
Low (Stable Process) |
Efficient Supply Chains Sea
Transport |
Sensitive Supply Chains Sea-Air
Transport |
High (Development Process) |
Supply Chains with Risk Coverage Sea
Transport |
Agile Supply Chains Air
Transport |
Figure 3: Supply Chain Strategies and Transport Source: Lee, (2002) |
Reading
the matrix it is possible to confirm two parameters: Functional Products are
adaptable to sea transport with lower transport costs and Innovative Products
are much more adaptable to Air Transport with higher transport costs.
Lower Transport Costs versus
Higher Transport Costs is a question been made all over the world on each model
of supply chain management. Transport is one of the most import supports of
supply chains, especially when considering 1/3 of total costs are transports
(Oliveira, 2009)
MIC is formed by different supply chain models and its
characteristics, which considers innovative and functional products in a
proportion of: functional products 55% and innovative products 45% of total
revenue. This means MIC needs to be global competitor for both: innovative and
functional products.
Reconciling the current customs legislation with the
process for making procedures more agile has been the greatest difficulty faced
in effectively implementing this Consigned Stock Model in the MIC. While the
agile management model predicts just a few hours for the unloading of
international merchandize, the MIC works with a number of working days for the
complete transportation and unloading of imported merchandize, if it uses the
consigned stock model.
There is a need to consider, however, that the strategy
of consigned stock in the Manaus Industrial Center was required given the type
of company, with innovative products and unstable demand. The need to attend
the market, with greater speed and variety in comparison with the other
companies, led to the development of a management model that makes the imported
raw materials available close to the factory, with a view to fast action in the
case of sharp changes in demands.
On the other hand, simply increasing the security stock
is also not a solution, since the cost involved in storing raw material is
impracticable and the aggregated value of the raw material held in stock is
very high. This is why there is a need to adapt logistics strategies and customs
legislation for this type of product, if we intend to keep investments of this
type of company in the MIC.
However, when we analyze the supply chains in the
uncertainty model, with all its need for agility in the processes and knowing
that good logistic chain management is one of the pillars for the good
development of an industrial unit, we ask whether the factors of fiscal tax
attractiveness are enough, or whether the benefit of logistical agility is
equally vital to the attractiveness and good development of the industrial
model for uncertain supply chains.
6
CONCLUSIONS
AND RECOMMENDATIONS
The difficulty in supply chain management for the
representatives in the Uncertainty Model was the reason for this article, which
sought to discuss how transport could be adapted the Uncertainty Supply Chain
Model and how it would help to develop MIC to be a global competitor even far
from supply basis, for example west versus east.
In this sense, air transport is a fundamental
pre-requisite for attending the supply chains in the uncertainty model, for
innovative products which are 45% of total revenue for this model.
It needs to have an improved infrastructure and guarantee
the agility and attractiveness of this model of high aggregated technology also
in the Manaus Industrial Center (MIC).
With the MIC being one of the foremost export centers in
Brazil, there is a need to improve the services and infrastructure for air
transport as a fundamental support for developing high technology production
and, consequently, products on the cutting edge of technology, which could
contribute greatly to the level of Brazilian exports, given their high
aggregated value.
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Paulo: Atlas.
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Suprimentos. São Paulo: Atlas.
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Paulo: Atlas.
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Electronic Marketplaces: a literature review and a call for supply chain
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Research.
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Aligning Supply Chain Strategies with Product uncertainties. California
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Industriais. Manaus: SUFRAMA, acessado em: agosto de 2008, acessado em: http://www.suframa.gov.br.