Supply Chain Management and Logistics in Latin America

This note explores the applicability of evaluation criteria to the problem of evaluating the supply chain strategy (SCS) of an organization. A discussion of SCS evaluation is relevant today, as the validity of the dominant approach – proposed two decades ago and based on matching types – has come into question. While evaluation criteria have a long history in other disciplines, they are new to SCS evaluation. To help supply chain (SC) scholars assess the applicability of evaluation criteria to SCS, this note proposes a tentative set of criteria and provides insights derived from the authors’ recent experience. We propose that the use of criteria for the evaluation of SCS may be a useful alternative, or at least a complement, to the dominant approach. These proposed criteria are currently being validated in a project with a company in Uruguay; we invite further empirical validation by third parties.

This chapter proposes a hybrid heuristic method combining a clustering search (CS) metaheuristic with an exact algorithm to solve a two-stage capacitated facility location problem (TSCFLP). The TSCFLP consists of defining the optimal locations of plants and depots and the product flow from plants to depots (first stage) and from depots to customers (second stage). The problem deals commonly with cargo transportation in which products must be transported from a set of plants to meet customers’ demands passing out by intermediate depots. The main decisions to be made are related to define which plants and depots must be opened from a given set of potential locations, which customer to assign to each one of the opened depots, and the amount of product flow from the plants to the depots and from the depots to the customers. The objective is to minimize costs satisfying demand and capacity constraints. Computational results demonstrate that our method was able to find good solutions when comparing it directly with a commercial solver and a genetic algorithm (GA) reported in a recent chapter found in the literature, requiring less than 1.5% and 41% of the computational time performed by these methods, respectively. Thus, our hybrid method combining CS with an exact algorithm can be considered as a new matheuristic to solve the TSCFLP.

Waste production is one of the most important problems that humankind faces. Human-based activities generate diverse waste types that have to be treated and disposed differently. This results in the need to build more facilities to manage the waste and to avoid further environmental damage. Colombia established a successful policy to close open dumps and to control pollution. Notwithstanding the advances that have been made in final disposal, it is necessary to extend the life of the final disposal sites and increase the closure of open landfills. Valle del Cauca is the third most populated Colombian province, and it is also considered the third province that generates more waste. This chapter addresses the problem of locating solid waste disposal centers in Valle del Cauca by applying the analytic hierarchy process (AHP) with fuzzy logic, a multicriteria method that compares opinions of a decision-making group. Additionally, each potential location area is characterized by considering industrial and environmental issues, societal dynamics, infrastructure and topography, costs, and taxes. After applying a variant of AHP, the decision-making group was able to find that Jamundi is the best location to open the disposal center. The method shows strong potential to identify and prioritize alternative locations for a diverse group of stakeholders. Most importantly, the methodology lets us structure better qualitative and quantitative data, as well as to link multiple levels to avoid choosing locations that will affect society, environment, and other stakeholders, without considering the trade-offs among diverse criteria considering benefits, opportunities, costs, and risks (BOCR).

Since the sixteenth century, Panama has been an important logistic node for communication between South America, North America, and Europe for trade and load transit. Panama ports move more than 700 million tons per year while Panama Canal moves 325,428,407 tons, according the statistics of 2014. Most of the maritime cargo moved through Panama is transit and transshipment cargo. Consequently, and due to the geographical position and future opportunities based on the expansion of the Panama Canal, Panama could be a strategic hub of global trade flows. This is an opportunity to develop value-added logistics services (VALS) in Panama Canal. Thus, this research aims to present a preliminary analysis of VALS industry in Panama, identifying critical variables that could enhance these services. This is a survey-based research, using interviews with the main suppliers of VALS in Panama and some of their customers. The methodology applied to analyze the data is means-end value hierarchy model (MEVHM), which was used to understand VALS industry in Panama and identify what is valuable to customers. Results showed that each VALS provider serves a mean of 20 companies, 22% of them are national clients while 78% are international clients, which recognized the geographical position as their main reason to work with logistics experts from Panama. Furthermore, 92% of them were very satisfied or satisfied with the service received. Main VALS in Panama are labeling, tagging, and packaging. In contrast, areas to be improved are customs procedures, national logistics processes, product’s traceability, competitive prices, and human resources training.

The last mile of parcel deliveries is a key process to service providers, with global costs that reach up to 70 billion euros per year. Moreover, due to urban population growth and to the rise of e-commerce, the importance of last-mile deliveries and its impacts to the environment and quality of life in cities tend to increase even more. This chapter proposes a more comprehensive methodology to assess alternative last-mile distribution strategies in terms of environmental and economic aspects and presents an application to the distribution of a postal company located in the city of Rio de Janeiro, Brazil. We evaluated the use of small electric vehicles (i.e., tricycles) in the last mile deliveries by assessing two scenarios: (1) the baseline scenario using a light commercial vehicle and (2) a scenario using electric tricycles. Results indicated that the use of electric tricycle is a more feasible alternative regarding the economic and environmental aspects as well as to maintain the service level of the company.

The fast growth of urban areas in major cities worldwide is undoubtedly one of the biggest concerns for city officials. In Latin America, data show that currently 81% of its inhabitants live in urban areas, and calculations forecast an increase in this percentage. In this context, urban logistics would become increasingly important in the overall performance of the region and its cities. The main objective of this study was to develop a set of key performance indicators (KPIs) to complement the square kilometer (km²) methodology developed by MIT, applying it in a highly intensive HORECA (hotels, restaurant, coffee shops) area known as “Zona T (The T Zone)” in Bogotá, Colombia, as this is a critical area where distribution needs to be performed at its best. Data such as shop inventory (stores, restaurants, drugstores, etc.), vehicle counting (cars, buses, motorbikes, trucks, etc.), product deliveries (by type: perishables, groceries, cleaning supplies, etc.), and traffic disruptions were collected through observation. Based on literature review and results of the study, 13 KPIs are proposed in three categories: operational (average distance and store coverage, service time & service rate, store density, delivery points, easiness for delivery and vehicle delivery factor), energy and environmental (fuel consumption and emissions), and traffic (traffic density, speed and traffic per lane). The main results show a 62-m average distance from truck to store, service time of 18:36 min, 1.019 gal and 9.1 kg CO₂e of fuel consumption and emission, respectively, traffic density of 421 vehicles/h, and other results described throughout the document.

While in some districts having drinking water is a given reality, there are others where there is a lack of access to this resource. Unfortunately, even today, 10.2% of the world population lives this situation and it could be worse in the coming years, according to UNICEF. Inhabitants in Pamplona Alta at southern Lima, Peru, daily suffer this harsh reality. This social challenge study attempts to define a methodology for an effective logistic planning of water distribution in Torres Minas. Currently, they obtain it from unsanitary and informal vendors. This chapter provides the basis of a new layout of the water distribution network based on clusters to efficiently satisfy water demand. Specifically, we propose the use of orderly delivery points called “bus-stops of water” in a two-echelon distribution system, whose optimization relies on a mixed-integer linear programming (MILP) technique. The objective of these guidelines is minimizing the transactional and transportation cost, while increasing the bargaining power of the community. Results showed a reduction of 52.67% and 26% in transactional and transportation costs, respectively, and a reduction of the associated risks of shortage and contamination of a tight delivery of water. Moreover, we foster the application of this methodology in other similar situations to produce sustainable growth for human settlements; regardless, there is a lack of access to water or a steep geography.

This chapter describes and discusses the main results of the successful off-hour delivery (OHD) pilot test in the city of São Paulo, Brazil, which took place between October 2014 and March 2015. The pilot engaged major stakeholders in urban distribution, including local authorities, shippers, carriers, and receivers, with the aim to determine what are the main requirements, constraints, opportunities, and threats for establishing a public policy related to shifting deliveries to late night in order to mitigate traffic congestion.

Differently from the former City of New York OHD pilot, here all participant companies were volunteers, with no need for cash incentives. The primary focus in São Paulo was on the issues of safety and noise, besides productivity aspects of travel time, truck speed, and delivery time.

The pilot was very successful, with no registered complaints of noise or security incidents. Travel speeds were obtained from global positioning system (GPS) tracking data and internal delivery systems. The chapter compares daytime and night operations and shows that productivity in some chains would improve significantly, but noise and safety must be carefully controlled to guarantee the expansion of the concept.

Demand for goods/services has increased in Latin America due to urbanization, leading to a complex delivery system and increased logistical activities. In Quito, the Historic Center and La Mariscal are two zones that face logistical challenges. The objective of this chapter is to analyze the commercial logistic activities related to loading and unloading goods in these zones. To address this urban freight problem, this chapter proposes a solution through the calculation of the optimal number and location of loading and unloading bays in each zone based on actual commercial activity data. First, a delivery survey was completed in each zone regarding frequency and amount of deliveries. Then, based on the data obtained, an optimization model is proposed to determine the optimal number and location of loading and unloading bays. Finally, a simulation model of the delivery process is performed to readjust the bay’s optimal number. A total number of 75 and 98 bays were calculated to serve the total shopping district of a representative square kilometer (km²) of the Historic Center and La Mariscal. This solution aims to minimize the delivery time and the distance for deliveries, improve urban freight transportation, and reduce traffic. This study could be used as a baseline and guide for further research in urban logistics, especially in Latin America, where urban logistics is still under study. This chapter is part of a Research Project of Urban Logistics in Quito, led by Universidad San Francisco de Quito (USFQ), in association with the Megacity Logistics Lab of MIT.

The objective of inventory management models is to determine efficient policies for managing the trade-off between customer satisfaction and the cost of goods. This chapter presents a methodology that uses the Monte Carlo Method (MCM) to estimate the behavior of a raw material supply model, considering uncertain variables such as demand, prices, and exchange rates. In order to show how to use this methodology, we analyze the case of a Colombian company in the aluminum industry. This company imports aluminum sheets from China. In this case, we analyze the financial impact of the raw material supply contract proposed by the Chinese supplier. The model considers different supply scenarios for the raw material. We calculate robust indicators such as Value at Risk (VaR), the Conditional Value at Risk (CVaR) and the probability of success for each scenario analyzed. Finally, we conduct a sensitivity analysis with respect to the sales price to validate the proposed models and solution approaches. The results show that considering risk metrics to evaluate the impact of endogenous factors over the supply process is a useful approach to improve decision-making related to this process and also can help to ensure the profitability of the company.