Supply chain performance measurement
in Latin America
*IMT
http://www.imt.mx/
Gaston Cedillo Ph.D.
National Council of Science & Technology, Mexico
AGENDA
2
1. General context;
2. Data availability and coverage;
3. Measurement approaches;
4. Analysis based on logistics chains: An UN-ECLAC perspective;
5. Supply chain clustering: A new paradigm?;
6. Takeaways.
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General
context
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REGIONALIZATION OF SOURCING BASIS
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© Global Manufacturing Competitiveness Index (2013)
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© Supply Chain Digest (2013)
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RELIABILITY OF LOGISTICS PERFORMANCE
The impact of specific improvements in logistics performance (time, cost,
and reliability) on increased trade.¹
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¹ Hausman, Lee and Subramanian (2013). “The Impact of Logistics Performance on Trade”.
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Production and Operations Management, Volume 22, Issue 2, pages 236–252.
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REGIONALIZATION
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© Jean-Paul Rodrige (2010)
1
0
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© Branco, Cabral, Kraiselburd, Silva and Witty (2014)
Data
(analysis)
1 1
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availability and
coverage
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KEY ISSUE
Competitive Strategy
Supply Chain
Strategy
Efficiency
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Cross
Functional
Drivers
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Supply chain structure
Responsiveness
Facilities
Inventory
Transportation
Information
Sourcing
Pricing
© Chopra and Meindl (2013)
Logistical
Drivers
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SUPPLY CHAIN PERFORMANCE MEASUREMENT
STUDIES
• No alignment between a national competitive strategy and supply
chain strategy;
• No statistical significance / methodology is not clearly exposed;
• Public approach are not part of the analysis;
• No private - public collaboration (for sharing data).
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Measurement
Approaches
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© 2012 *GC
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AN ACADEMIC PERSPECTIVE
Objective
─ To identify methodologies when performing research in supply chains.
Analysis:
─
─
─
─
─
Theory building;
Surveys;
Case studies;
Action-Research;
Modelling
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© Kotzab, Seuring, Müller and Reiner (2005)
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AN ACADEMIC PERSPECTIVE
Objective
─ To identify methodologies when measuring supply chain performance
under a manufacturing context in emerging markets;
Method:
─ Literature review (95 papers);
─ Database integration;
─ Statistical analysis (SPPS).
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© Avelar-Sosa, García and Cedillo-Campos (2014)
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AN ACADEMIC PERSPECTIVE
Discriminant analysis
25
Structural equations
20
Neural hierarchy process
15
10
Empirical analysis
Design of experiments
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0
Descriptive analysis
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Liner regression
Factorial exploratory
analysis
Simulation
Analytic hierarchy process
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© Avelar-Sosa, García and Cedillo-Campos (2014)
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AN ACADEMIC PERSPECTIVE
Main findings
─ Two different perspectives: i) financial; ii) operational;
─ Most of the papers used only one methodological approach;
─ The use of more than an approach to measure SC performance is
increasing;
─ More attributes are currently being integrated to SC performance
analytics.
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© Avelar-Sosa, García and Cedillo-Campos (2014)
LatAm perspective
Logistics Cost
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CHALLENGES INCREASING LOGISTICS COSTS
─ Infrastructure scarcity;
─ Low logistics connectivity;
─ Multidimensional issues at border crossings;
─ Regulatory rigidities;
─ Informality of transport and logistics providers;
─ Differences in regulations;
─ Security issues;
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─ Low visibility along the supply chain
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© Sanchez et al. (2014)
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LATAM EXPORTS BY REGION
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© UN-ECLAC (2012)
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LATAM EXPORTS INTRA REGION
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© UN-ECLAC (2012)
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MEXICO
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© Observatory of Economic Complexity (2012)
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BRAZIL
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© Observatory of Economic Complexity (2012)
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TRADE FACILITATION INDICATORS
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© UN-ECLAC-NRID, based on Doing Business (2013)
TARIFF VS. TRANSPORT COSTS
% exports
2
6
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10% reduction on tariff costs
10% reduction on transport costs
© World Bank, UN-ECLAC and IDB (2010)
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COST CATEGORIES
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© Perez-Salas et al. (2014)
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PROPOSED APPROACH: ANALYSIS OF LOGISTICS CHAINS
1. Selection of logistics chains;
a. Map of relevant logistics chains;
b. Selection of logistics chains;
c. Definition of cost categories;
d. Identification of information sources;
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© Pérez-Salas et al. (2014)
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PROPOSED APPROACH: ANALYSIS OF LOGISTICS CHAINS
2. Cost and over cost analysis;
a. Map of relevant logistics processes;
b. Cost and over cost analysis to every logistics chain;
c. Analysis of logistics inefficiencies and its impact by economic sector
as wells as to national competitiveness;
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© Pérez-Salas et al. (2014)
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PROPOSED APPROACH: ANALYSIS OF LOGISTICS CHAINS
3. Recommendations and proposals to improve public policies;
a. Analysis and recommendations;
b. Conclusions;
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© Pérez-Salas et al. (2014)
Supply chain clustering
The next logistics paradigm?
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© 2013 *GC
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2
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INDUSTRIAL SECTOR
7th Global car-producing country
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AUTOMOTIVE INDUSTRY
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AUTOMOTIVE SUPPLY CHAINS
Raw materials
suppliers
Suppliers
Tier 2
Mexico
Mexico
Mexico
Distribution
centers
Mexico
Mexico
Mexico
Mexico
Suppliers
Tier 1
Assembly
plants
After
Market
Mexico
Mexico
Mexico
USA
USA
Brazil
Germany
Mexico
Mexico
China
Mexico
Mexico
USA
USA
Mexico
Mexico
USA
Mexico
Mexico
USA.
China
Mexico
Brazil
USA
Mexico
Germany
Germany
Mexico
China
Mexico
Mexico
China
Mexico
Mexico
Mexico
Mexico
Mexico
USA
USA
Mexico
USA
Germany
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Mexico
USA
Mexico
Mexico
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Mexico
Mexico
USA
USA
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AUTOMOTIVE SUPPLY CHAINS
Selling to:
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Supplying to:
GM
Ford
Chrysler
Chrysler
56
64
-
Ford
51
-
54
GM
-
70
66
Asian OEM
58
65
59
European OEM
37
46
44
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© FT Deutschland, The Economist, CSM Worldwide, February-March (2009)
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© Sturgeon et al.. (2007)
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SUPPLY CHAIN CLUSTERING
Cluster
n-1
Cluster
n
Cluster
n+1
Global
Supply Chain
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Region n-1
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Region n
Region n+1
© Gaston Cedillo (2012)
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SUPPLY CHAIN CLUSTERS
Los Ángeles
Phoenix
Mexicali
Tijuana
S. Luis Río Colorado
Tucson
Cd. Juárez
Ensenada
Nogales
El Porvenir
EE.UU.
Ojinaga
Houston
Ciudad Acuña
San Antonio
Hermosillo
Chihuahua
Piedras Negras
Cuauhtémoc
Corpus Christi
Guaymas
Cd. Obregón
Nuevo Laredo
Monclova
Navojoa
Reynosa
Ahome
Gómez
Palacio
Guasave
Topolobampo
Matamoros
Monterrey
Saltillo
Torreón
Culiacán
La Paz
Durango
Ciudad Victoria
Mazatlán
Fresnillo
Zacatecas
Cabo San Lucas
S. Luis Potosí
Cancún
Guanajuato
San J uan
del Río
Puerto Vallarta
Salamanc a
Zamora
Colima
Manzanillo
Cd de
México
Papantla
Tlaxcala
Uruapan
Córdoba
Toluca
Lázaro Cárdenas
Nodos logísticos principales
Tuxtepec
Chilpancingo
Acapulco
Nodos logísticos secundarios
S. Andrés
Tuxtla
Cuernavaca
P uebla
Tehuacán
Ciudades principales
Playa del Carmen
Campeche
Xalapa
Veracruz
Macroámbitos funcionales
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Oaxaca
Coatzacoalcos
Reforma
Minatitlán
Huimanguillo
Tuxtla
Gutiérrez
Chetumal
Cd del Carmen
Villahermosa
El Ceibo
Belice
Ocosingo
San Cristóbal
de las Casas
Salina Cruz
Arrriaga
Relaciones logísticas consolidadas
Mérida
Poza Rica
Pachuca
Celay a
Morelia
Progreso
Tuxpam
Querétaro
Silao
Irapuato
LEYENDA
Altamira
Tampico
Ciudad
Vallés
Aguascalientes
Tepic
Guadalajara León
Guatemala
Tapachula
Honduras
Ciudad Hidalgo
El Salvador
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© ALG (2013)
SUPPLY CHAIN CLUSTERING
4
0
Logistics
Platform
Logistics
Platform
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Supply Chain Clustering
HUB
Supply Chain Clustering
HUB
© Gaston Cedillo (2013)
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AUTOMOTIVE PRODUCTION
US $ 10 billion
US $ 2 billion
US $ 1 billion
4
1
US $ 200 million
US $ 1 billion
US$ 3 billion
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© Brookings Institution (2014)
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KEY ISSUE
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DISRUPTIONS PROPAGATION
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CROSS-BORDER EFFECT
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TAKEAWAYS
─ Cost remains critical;
─ Supply chain reliability is now a key element of economic
performance;
─ A systems approach to improve LatAm supply chain performance
(reliability in time, cost, and service) is critical;
─ As a result of economic regionalization, Could be Supply Chain
Clustering another element in measuring supply chain performance?;
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─ Serious effort has to be done for improving reliability when performing
data collection and analytics.
http://www.imt.mx/
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GASTON CEDILLO
[email protected]
http://www.imt.mx